Impacts of Environmental Muck Dredging 2014-2015

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Final Project Report to Brevard County Natural Resources Management Department Funding provided by the Florida legislature as part of DEP Grant Agreement No. S0714 – Brevard County Muck Dredging

Project Manager: John G. Windsor Principal Investigators: Charles Bostater, Kevin B. Johnson, Jonathan Shenker, John H. Trefry, and Gary A. Zarillo Indian River Lagoon Research Institute Florida Institute of Technology Melbourne, Florida

July, 2016

Cover Image: Contour map of muck thickness in Turkey Creek from the adjacent Indian River Lagoon (IRL) to the Florida East Coast (FEC) railroad bridge. (Courtesy of Robert Trocine)

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Impacts of Environmental Muck Dredging 2014-2015

Final Project Report Submitted to Brevard County Natural Resources Management Department 2725 Judge Fran Jamieson Way, Building A, Room 219 Viera, Florida 32940 Funding provided by the Florida legislature as part of DEP Grant Agreement No. S0714 – Brevard County Muck Dredging

July, 2016

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute of Technology Final Report, July 2016

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Investigation of the Impacts of Environmental Muck Dredging in the Indian River Lagoon

Indian River Lagoon Research Institute Florida Institute of Technology, Melbourne, FL 32901

Executive Summary

In order to address serious water quality issues associated with muck sediment in the Indian River Lagoon, the Florida Legislature in the 2014 session directed one million dollars to the Florida Institute of Technology through Brevard County to investigate the effects of environmental muck dredging in the Indian River Lagoon. A collaborative interdisciplinary effort, through the Indian River Lagoon Research Institute (IRLRI) at Florida Institute of Technology, developed five research projects to help better manage future muck sediment removal efforts throughout the state of Florida: (1) Muck Dredging Research Project Management, (2) Biological Responses to Muck Removal, (3) The Efficiency of Muck Removal from Indian River Lagoon and Water Quality after Muck Removal, (4) Movement Measurements of Muck and Fluidized Mud at Dredge Sites, and (5) A Hydrologic and Water Quality Model for Management and Forecasting within Brevard County Waters of Indian River Lagoon. Reported here are results of those investigations.

1. Muck Dredging Research Project Management Five interdisciplinary projects developed by the Indian River Lagoon Research Institute (IRLRI) at Florida Institute of Technology are coordinated through the muck dredging research project management office: (1) Muck Dredging Research Project Management, (2) Biological Responses to Muck Removal, (3) The Efficiency of Muck Removal from Indian River Lagoon and Water Quality after Muck Removal, (4) Movement Measurements of Muck and Fluidized Mud at Dredge Sites, and (5) A Hydrologic and Water Quality Model for Management and Forecasting within Brevard County Waters of Indian River Lagoon. Regular meetings of the Florida Institute of Technology Environmental Muck Dredging (FIT-EMD) research principal investigators with representatives from Brevard County Natural Resource Management Department, Florida Department of Environmental Protection and St. Johns River Water Management District, and a team of external scientific consultants facilitate the exchange of scientific findings among all the investigators and optimize the outcomes of these research investigations. In addition, the project management office engages the public about muck dredging research through presentations open to the public and through social media.

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2. Biological Responses to Muck Removal Muck at the bottom of the Indian River Lagoon (IRL) creates an inhospitable environment for plants and animals. In addition, indirect effects of muck, such as nutrient flux into overlying waters can fuel algal blooms, creating stress on pelagic and benthic organisms. As muck is removed from the IRL through environmental dredging efforts, it is essential that we document post-dredge vs pre-dredge ecological conditions, confirming whether or not selected benthic and pelagic components of the IRL system are enhanced. This report details the monitoring of key biological populations (seagrasses, drift algae, invertebrate infauna, and fishes) in Turkey Creek (City of Palm Bay, Brevard County) and the adjacent IRL targeted for environmental muck dredging, as well as in control areas in the IRL for comparison.

Biological data were generally collected monthly through the duration of this study (May 2015- December 2015). Data have been collected and analyzed on the occurrence of seagrass (Halodule wrightii) and drift algae, including their % cover, canopy heights, % occurrence, and biomass. H. wrightii was not present in transect sampling within Turkey Creek, nearest the planned dredge site. H. wrightii was most abundant, when present, in the shallower nearshore portions of transects (40-70 cm depth) within the adjacent IRL, and generally declined in October and December, 2015. In contrast, drift algae, comprised mostly of Gracilaria spp. and one or two other abundant species, were most abundant in Turkey Creek, relative to the sites in the IRL proper. Drift algae were most abundant in May 2015 in Turkey Creek and the adjacent lagoon area. Drift algae were more pervasive temporally and spatially compared to seagrasses, but did decline in the winter; nearly absent in the December 2015 sampling. In addition, the abundances and distributions of 59 species of invertebrate benthic infauna were determined via surface sediment grabs. Sediments were evaluated with regard to grain size and organic content, and for correlations between those two sediment properties and species diversity and richness. Richness and diversity of infaunal invertebrate communities were greatest at the IRL sites, almost nil within muck, and intermediate in Turkey Creek adjacent to the planned dredge site. Sediments at these sites displayed a gradient of Fine-Grained Organic-Rich Sediment (FGORS) characteristics, which co-varied with the occurrence of certain species and with the diversity and richness patterns. Diversity and abundance are greater in cleaner sediments with relatively low FGORS scores.

Fish populations, abundances and distributions, were also determined via monthly seine net sampling. Pelagic schooling anchovies (Anchoa spp.) comprised 92.2% of the entire seine catch, which reflects the typical numerical dominance of these fishes within the IRL system. The high variability in anchovy catches reflect the patchy distribution of the schools and their movement into and out of Turkey Creek. Demersal juvenile fishes were dominated by mojarras (Eucinostomus spp. and Diapterus spp.; 3.2% of the total catch), and the important commercial/recreational fisheries family Sciaenidae (including silver perch, red drum, Atlantic croaker, spot, sea trout and kingfish; 2.3% of the total catch). The temporal patterns of

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016 abundance of these juveniles are influenced by the temporal and spatial patterns in adult spawning behavior. These baseline data will enable us, once dredging in Turkey Creek has occurred, to make comparisons in biological populations and communities before and after environmental muck dredging.

3. The Efficiency of Muck Removal from the Indian River Lagoon and Water Quality after Muck Removal Muck removal is an integral part of the restoration process in the Indian River Lagoon (IRL) system. This fine-grained, organic-rich material (muck) (1) is easily resuspended to increase turbidity, (2) consumes oxygen, (3) creates an inhospitable benthic habitat, (4) serves as a reservoir for potential pollutants and (5) is an internal source of dissolved nitrogen and phosphorus that diffuse into lagoon waters at a rate commensurate with external sources in the North IRL. This study began in February 2015 with a muck survey of Turkey Creek in advance of proposed dredging during 2016. Little or no muck was present in the adjacent IRL near the mouth of Turkey Creek in contrast with layers that were 1- to 3-m thick throughout most of the lower creek. The estimated total volume of wet muck in the creek from this study is 111,000 m3 (145,000 yd3). Muck sediments from the creek contained >75% water by weight (>90% water by volume), 76- 99% silt + clay, and 11-22% organic matter (4-7% organic carbon, 0.4-0.8% organic N and 0.10- 0.17% total phosphorus). These values match earlier characterizations of muck deposits.

Water quality surveys were carried out monthly from April to December 2015 at five stations. Continuous profiles for salinity, temperature, dissolved oxygen and pH were obtained and 2-5 discrete water samples were collected at each station (135 total samples over 9 months). Water samples were analyzed for (1) turbidity (NTU) and total suspended solids (TSS in mg/L), (2) total concentrations of particulate iron, aluminum, silicon, nitrogen, phosphorus and organic carbon and (3) concentrations of dissolved ammonium, nitrate + nitrite, organic carbon, phosphate, total nitrogen and total phosphorus. Data from the water quality surveys will be used in the post- dredging assessment of the effectiveness of muck removal.

The average chemical forms of nitrogen in the water column (n = 135 samples), with percent of the total nitrogen in parenthesis, were as follows: dissolved organic nitrogen (57.8%), particulate organic nitrogen (32.1%), ammonium (8.9%) and nitrate + nitrite (1.2%). Large spikes in concentrations of ammonium (up to 50 µM or 0.7 mg N/L) were found in small depressions in Turkey Creek and linked to releases from muck sediments. These high values were ~10-fold greater than median concentrations of ~5 µM (0.07 mg N/L) in the overall study area. Concentrations of nitrate + nitrite were regularly higher in fresher water near the Florida East Coast railroad bridge (4-6 µM; 0.06-0.08 mg N/L) relative to average values near the mouth of Turkey Creek of ~1 µM (0.014 mg N/L).

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For phosphorus, the chemical forms in the water column (n = 135 samples), with percent of the total phosphorus in parenthesis, averaged as follows: particulate organic phosphorus (48.7%), phosphate (29.7%) and dissolved organic phosphorus (21.6%). Concentrations of dissolved phosphate as high as 10 µM (0.31 mg P/L) were found in the same small depressions with high ammonium values. These phosphorus spikes also were linked to releases from muck sediments. The median phosphate value in Turkey Creek was 0.8 µM (0.025 mg P/L). The lowest concentration of dissolved phosphate was 0.03 µM (0.0009 mg P/L) in the adjacent IRL during December.

Tracking changes in fluxes of nitrogen and phosphorus from muck sediments is an important part of the post-dredging assessment. Fluxes of nitrogen (essentially all as ammonium) and phosphorus (essentially all as phosphate) from muck sediments averaged ~ 10 and 1 metric tons/km2/yr, respectively, with a large contribution to bottom water ammonium and phosphate concentrations.

The post-dredging assessment of the effectiveness of muck removal from Turkey Creek will include the following components: (1) a muck survey, (2) determination of the composition of remaining sediment in the creek after dredging, (3) comparison of pre- and post-dredging concentrations, forms and distribution of selected water quality parameters, especially dissolved oxygen, particulate organic carbon and dissolved and particulate nitrogen and phosphorus and (4) determination of nitrogen and phosphorus fluxes from bottom sediment to the water column.

4. Movement Measurements of Muck and Fluidized Mud at Dredge Sites Muck is typically greater than 75% water by weight (Trefry et al., 1987) and like water, it moves as fluid mud (Mehta et al., 1994) when disturbed by wind waves and currents. The purpose of measuring muck and fluidized mud movement is to provide management information that can be applied to calculate the mass of moving particulate material just above the bottom. This moving dense fluid is a “carrier” of nutrients. Data concerning the magnitude of moving muck and fluid mud in terms of transport fluxes in bottom waters can be used in calibration of sediment and water quality models.

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016 verified by sludge judge measurements of muck depths greater than 3 m. Stokes drift velocity (Craik, 2005) concerning residual upstream bottom transport also supports this westward (upstream) movement of particulates in the bottom boundary layer. The Stokes drift velocity in Palm Bay would be westward due to westward propagating wind driven gravity waves when the wind blows from east to west. Stokes drift theory in shallow bottom waters suggests that moving fluid mud and muck from outer Palm Bay will thus likely contribute to buildup of muck in the deep dredged area east of US1.

Particulates moving into the sondes located in the moving lutocline and nepheloid layers include estuarine flocs (colloidal aggregates). These fine grain flocs were clearly observable in optical and acoustic imagery. The irregular size of these floc aggregates was quantitatively analyzed and described. The magnitude of the floc material collected by the sondes within the moving fluid mud is similar to prior research in the Indian River Lagoon (Bostater and Rotkiske, 2016. Image analysis of flocs indicated predominant effective diameters of 0.1 mm to 10.2 mm. Mean cross- sectional floc diameter was 2.77 mm (2770 μm) ± 2.44 mm SD with a median floc effective cross-sectional area of ~30 mm2. These particulates do not settle according to Stoke’s law for individual particle settling. Stokes settling law applies only for laminar flows and spherical particles.

Area wide station analysis utilizing all flux density sonde results indicate different magnitudes of material moving (1) west of the railroad bridge, (2) east of US1 and within Palm Bay, and (3) at the mouth of Palm Bay and nearby Indian River Lagoon. Station sonde fluxes at the mouth of Palm Bay were greater than 1200 g m-2 day-1. A net upstream flux (towards Palm Bay and west of US1) in the lower 0.5 meter water column transect across the mouth of Palm Bay was measured. The total dry weight moving muck collected across a transect of six stations at the mouth of Palm Bay indicated a net upstream movement 93,000 g day-1 (~34,000 kg yr-1). This net upstream result is also consistent with a Stokes drift towards US1 during the sampling period.

Area wide GIS spatial analysis demonstrates that sonde data processed in a gridded manner could be applied in modeling water quality and sediments. The gridded state variables include transport fluxes of particulate organic matter, particulate inorganic matter, particulate organic nitrogen, particulate organic phosphorus and particulate organic carbon movement. The data from this project estimated nutrient transport fluxes within the moving muck by utilizing muck-nutrient relations developed by Trefry, 2015.

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Rotkiske and Bostater, 2016) to estimate the reduction in moving muck after dredging. In summary, data derived from the sondes can provide important sediment flux (mass transport) of sediments in the bottom boundary layer and the moving lutocline for future bottom sediment forecast modeling.

5. Hydrologic and Water Quality Model for Management and Forecasting within Brevard County Waters of the Indian River Lagoon A coupled hydrodynamic-water quality model of the Indian River Lagoon is designed as a tool for understanding the ecology, maintaining water quality goals, and forecasting the potential benefits of management strategies, including muck dredging. The overall goal is to integrate water quality and physical process data into the coupled model of the IRL for long-term calibrated and validated predictions of water quality. Questions to be answered include: 1) whether muck dredging will improve local water quality in the vicinity of Turkey Creek and other localities that are to be dredged over the next several years, 2) whether improved model guidance by measured in situ data and modeled watershed data will allow the relative effects of watershed inputs and nutrient flux from muck sediments to be resolved, 3) if muck dredging, either locally or regionally, can result in a lasting improvement of IRL water quality. Project tasks are aimed at evaluating the benefits of muck dredging in the north and central Indian River Lagoon, among other issues.

Model validation results show a good match between predicted and measured parameters such as salinity, temperature, water level, and dissolved oxygen. Model runs under various scenarios/cases were conducted to test potential water quality improvements that may result from muck dredging. Model Case 1 includes existing conditions with respect to watershed inputs, baseflows, and gauged freshwater flow into Turkey Creek from the C-1 control structure. Nutrient flux from the benthic boundary of Turkey Creek was set according to fluxes reported by Dr. John Trefry in Chapter 3 of this report. In the region surrounding Turkey Creek the flux was set to be equivalent to the IRL average. Model Case 2 assumed a 50% reduction in the ammonium-based nitrogen flux from muck sediment to the water column. Model results indicate a reduction of about 25% to 30% in total nitrogen concentration in the water column at the mouth of Turkey Creek after hypothetical reduction of ammonium flux based on muck removal. Model results also showed a detectable, but variable reduction of total nitrogen within 4 km of Turkey Creek entrance. A numerical (model) monitoring station in the IRL, 10 km to the south of Turkey Creek entrance, showed a detectible reduction in total nitrogen concentration for the first half of a 2-year model run. Other water quality variables are also calculated including forms of phosphorus, dissolved oxygen, and several others. These model data along with values for nitrogen components are stored in model data archives for further analysis.

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Table of Contents Executive Summary………………………………………………………………………………iii Table of Contents…………………………………………………………………………………ix

List of Figures…………………………………………………………………………………...xiii

List of Tables…………………………………………………………………………………..xxiii

Acknowledgements……………………………………………………………………………..xxv

Chapter 1 Muck Dredging Research Project Management ...... 1-1 1.1 Summary ...... 1-1 1.2 Introduction ...... 1.2 1.3 Approach ...... 1-4 1.4 Results ...... 1-7 Chapter 2 Biological Responses to Environmental Muck Dredging ...... 2-1 2.2 Introduction ...... 2-3 2.3 Approach ...... 2-5 2.4. Results and Discussion ...... 2-11 2.4.1. Results and Discussion – Seagrasses and Infauna ...... 2-11 2.4.2 Results and Discussion – Fishes ...... 2-27 2.5 Conclusions ...... 2-45 2.6 References ...... 2-47 Chapter 3 The Efficiency of Muck Removal from the Indian River Lagoon and Water Quality after Muck Removal ...... 3-1 3.1 Summary ...... 3-1 3.2 Introduction ...... 3-2 3.3 Approach ...... 3-4 3.3.1 Muck Survey, Sediment and Water Collection ...... 3-4 3.3.2 Laboratory Analyses: Sediments ...... 3-6 3.3.3 Laboratory Analyses: Water Dissolved Chemicals ...... 3-7 3.3.4 Laboratory Analyses: Water Particulate Chemicals ...... 3-9

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Table of Contents (Continued)

3.3.5 Quality Assurance and Quality Control (QA/QC) ...... 3-10 3.4 Results and Discussion ...... 3-12 3.4.1 Muck Survey...... 3-12 3.4.2 Muck Composition and Fluxes of Nitrogen and Phosphorus from Sediments ...... 3-15 3.4.3 Water Quality Surveys ...... 3-22 3.4.4 Chemical Forms of Dissolved and Particulate Nitrogen and Phosphorus ...... 3-37 3.5 Conclusions ...... 3-42 3.6 References ...... 3-44 Appendices ...... 3-47 Appendix A. Sampling grid and data from muck survey. Grids are identified by letter and number. Dimensions (N-S, 1 sec of latitude, 30.5 m) (E-W, 1 sec of longitude, 27.5 m). 3-47 Appendix B. Selected Quality Assurance and Quality Control Data ...... 3-56 Appendix C1. Concentrations of dissolved and particulate parameters for Stations 1-5 for April 22, 2015...... 3-62 Appendix C2. Concentrations of dissolved and particulate parameters for Stations 1-5 for May 4, 2015...... 3-64 Appendix C3. Concentrations of dissolved and particulate parameters for Stations 1-5 for June 16, 2015...... 3-66 Appendix C4. Concentrations of dissolved and particulate parameters for Stations 1-5 for July 16, 2015...... 3-68 Appendix C5. Concentrations of dissolved and particulate parameters for Stations 1-5 for August 26, 2015...... 3-70 Appendix C6. Concentrations of dissolved and particulate parameters for Stations 1-5 for September 9, 2015...... 3-72 Appendix C7. Concentrations of dissolved and particulate parameters for Stations 1-5 for October 14, 2015...... 3-74 Appendix C8. Concentrations of dissolved and particulate parameters for Stations 1-5 for November 23, 2015...... 3-76 Appendix C9. Concentrations of dissolved and particulate parameters for Stations 1-5 for December 14, 2015...... 3-78 Appendix D: Abstract accepted for Oral Presentation at Ocean Sciences 2016 ...... 3-80

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Table of Contents (Continued)

Chapter 4 Movement Measurements of Muck and Fluidized Mud at Dredge Sites

4.1. Summary……..…………………………………………………………………………..4-1

4.2 Approach…………………………………………………………………………………4-2

4.2.1 Conceptual Framework, Definitions, Methods………………………………………4-2

4.3 Results and Discussion …………………………………………………………………4-10

4.3.1 Sonde Station Deployment Results …………………………………………………4-10

4.4 Conclusions……………………………………………………………………………..4-28

4.5 Quality Assurance Plan for Task 4……………………………………………………...4-29

4.5. A. Project Purpose and intended use of data……………………………………………4.29

B. Brief historical overview and literature search……………………………………...4.30

C. Statement of anticipated results of the research project……………………………..4-31

D. Description of work to be conducted, including the types of analysis to be performed

to monitor the effectiveness of the research………………………………………...4-32

E. Quality Control and Measures……………………………………………….……..4-36

F. Documentation and Records………………………………………………………..4-39

G. Training Required For The Project …………………………………………………4-41

References…………………………………………………………………………………..4-41

Data Appendices…………………………………………………………………………….4-46

Appendix I – sonde derived data……………………………………………………....4-46

Appendix II – background data………………………………………………………..4-50

Chapter 5 Hydrologic and Water Quality Model for Management and Forecasting within Brevard County Waters of the Indian River Lagoon 5.1. Summary…….…………………………………………………………………………..5-1

5.2 Introduction and Goals …………………………………………………………………..5-2

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Table of Contents (Continued) 5.3 Methods ………………………………………………………………………………….5-2

5.3.1. Hydrodynamic Model Overview ....………………………………………………...5-2

5.3.2. Model Overview - Water Quality Calculations ..…………………………………...5-3

5.3.3. Spatial Watershed Iterative Loading (SWIL) model …………………………….....5-7

5.3.4. Hydrodynamic and Water Quality Model Grid Generation ………………………..5-7

5.3.5. Hydrodynamic Model Inputs ……………………………………………………...5-10

5.3.6. Water Quality Model Setup………………………………………………………..5-14

5.3.7. Watershed Inputs…………………………………………………………………..5-15

5.3.8. Sediment Diagenesis Model Setup for Muck Assessment………………………...5-17

5.4 Results ………………………………………………………………………………….5-19

5.4.1. Hydrodynamic Model Validation………………………………………………….5-19

5.4.2. Calibration of Physical Processes………………………………………………….5-19

5.4.3. Calibration of Transport Processes ………………………………………………..5-20

5.4.4. Calibration Statistics ………………………………………………………………5-21

5.4.5. Water Quality Model Validation …………………………………………………5-22

5.4.6. Model Simulations in the Central IRL ……………………………………………5-24

5.5 Project Quality Control …………………………………………………………………5-29

5.5.1. U.S. Geological Survey Hydrologic Data …………………………………………5-29

5.5.2. Quality Assurance for the SWIL Watershed model ………………………………5-30

5.5.3. Quality Assurance for SJRWMD water quality data …..…………………………5-30

5.6 Conclusions ….…………………………………………………………………………5-30

5.7 References ……………………………………………………………………………...5-32

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List of Figures Figure 2.1 Primary study sites…………………………………………………………………..2-7 Figure 2.2 Seagrass mean % cover…………………………………………………………….2-12 Figure 2.3 Seagrass mean visual % cover …………………………………………………….2-13 Figure 2.4 Seagrass mean shoot count………………………………………………………....2-14 Figure 2.5 Seagrass mean canopy height……………………………………………………....2-15 Figure 2.6 Drift algae mean % cover…………………………………………………………..2-16 Figure 2.7 Drift algae mean % biomass……………………………………………………….2-17 Figure 2.8 Drift algae mean canopy height……………………………………………………2-18 Figure 2.9 Sediment mean % water content………………………………………………….. .2-19 Figure 2.10 Sediment mean % silt+clay content……………………………………………....2-20 Figure 2.11 Sediment mean % organic matter………………………………………………...2-20 Figure 2.12 Sediment mean subjective sulfur odor…………………………………………....2-21 Figure 2.13 Mean infaunal biodiversity……………………………………………………….2-24 Figure 2.14 Mean infaunal species richness………………………………………………….. .2-24 Figure 2.15 Infaunal richness vs. sediment % organic matter………………………………....2-25 Figure 2.16 NMDS infaunal community analysis……………………………………………..2-25 Figure 2.17 Abundance of Foraminifera in Turkey Creek…………………………………….2-26 Figure 2.18 Turkey Creek Foraminifera abundance vs. sediment silt+clay content…………..2-26 Figure 2.19 Mean monthly density of anchovies (Anchoa spp.)……………………………....2-28 Figure 2.20 Mean monthly density of mojarras (Eucinostomus spp. and Diapterus spp.)……2-32 Figure 2.21 Water discharge at USGS station 02250030……………………………………...2-33 Figure 2.22 Sampling grid for FWCC Fisheries Independent Monitoring Program near Turkey Creek………………………………………………………………………..2-34 Figure 2.23 Length frequency distributions of mojarras (Eucinostomus spp. and Diapterus spp.) …………………………………………………………………………………………….…...2-35 Figure 2.24 Mean monthly density of silver perch (Bairdiella chrysoura)…………………...2-37 Figure 2.25 Length frequency distributions of silver perch (Bairdiella chrysoura)………...... 2-37 Figure 2.26 Mean monthly density of red drum (Sciaenops ocellatus)……………………....2-38 Figure 2.27 Length frequency distributions of red drum (Sciaenops ocellatus)……………...2-39 Figure 2.28 Mean monthly density of juvenile seatrout (Cynoscion spp.) ……………………2-40

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List of Figures (Continued)

Figure 2.29 Length frequency distributions of juvenile seatrout (Cynoscion spp.)…………...2-40 Figure 2.30 Mean monthly density of sheepshead (Archosargus probatocephalus)………...... 2-41 Figure 2.31 Length frequency distributions of sheepshead (Archosargus probatocephalus)….2-42 Figure 2.32 ANOSIM comparison of fish community structure between FIT and FWC sampling in Turkey Creek………………………………………………………………………………. 2-43 Figure 2.33 ANOSIM comparison of fish community structure between FIT sampling in Turkey Creek and FWC sampling in in FIM grid 360…………………………………………………2-44 Figure 2.34 ANOSIM comparison of fish community structure between FIT sampling in Turkey Creek and FWC sampling in in FIM grid 368…………………………………………………2-44 Figure 3.1. (A) Using a PVC pole to determine water depth and muck thickness, (B) map showing sampling locations for sediment (labelled A-I) and water (labelled TC1-TC5), larger scale maps are presented in Section 3.4.1, (C) pumping water for chemical analysis using a peristaltic pump with Tygon tubing, and (D) SEAL AA3 three-channel auto-analyzer for nutrient analysis………………………………………………………………………………………….3-5 Figure 3.2. Contour map of water depth in Turkey Creek from the adjacent Indian River Lagoon (IRL) to the Florida East Coast (FEC) railroad bridge. Dots show probing locations ...... 3-12 Figure 3.3. Contour map of muck thickness in Turkey Creek from the adjacent Indian River Lagoon (IRL) to the Florida East Coast (FEC) railroad bridge. Dots show probing locations . 3-13 Figure 3.4. Water depth in Turkey Creek versus (A) thickness of the muck layer, and (B) muck thickness plus water depth. Lines on (B) show where no muck is found (+ 0 m) and where muck + water depth is +1, +2 and +3 m relative to water depth...... 3-14 Figure 3.5. Contour maps for muck thickness in Turkey Creek and the adjacent Indian River Lagoon (IRL). Blue dots show where surface sediments were collected. Numbers on (A) show % water in sediments by volume and (B) % loss on ignition (LOI) at 550˚C for sediments...... 3-16 Figure 3.6. Contour map for muck thickness in Turkey Creek and the adjacent Indian River Lagoon. Blue dots show where surface sediments were collected. Pie graphs show grain size distribution at selected stations...... 3-17 Figure 3.7. (A) Sediment total organic carbon (TOC) versus sediment Loss on Ignition (LOI) at 550°C, (B) sediment total phosphorus versus sediment TOC, (C) sediment total nitrogen versus TOC and (D) sediment total phosphorus versus total nitrogen. Muck samples plot within the ovals on (B), (C) and (D). The molar ratio for the four muck samples is listed next to each oval. Solid lines and equations on each graph are from linear regression analysis, dashed lines show 95% prediction intervals, r is the correlation coefficient and p is the p statistic...... 3-18

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List of Figures (Continued)

Figure 3.8. (A) Sediment total iron (Fe) versus total aluminum (Al) and (B) sediment total silicon (Si) versus Al. Solid lines and equations on each graph are from linear regression analysis, dashed lines show 95% prediction intervals, r is the correlation coefficient and p is the p statistic…………………………………………………………………………………………3-19 Figure 3.9. Vertical profiles for (A) water content, (B) total organic carbon (TOC) and (C) total nitrogen plus ratios of the three components to aluminum (Al) for a sediment core from station TC4 (location in Figure 3.1)…..……………………………………………………………….3-20 Figure 3.10. Vertical profiles for (A) dissolved ammonium and (B) dissolved sulfide in sediment interstitial water at station TC5 on May 5, 2015 (location shown on Figure 3.1)…………..…3-21 Figure 3.11. Locations of water quality stations TC1-TC5 with average water depths at each station and contour lines for muck thicknesses from our February 2015 survey...... 3-22 Figure 3.12. Vertical profiles for (A) salinity, (B) temperature, (C) % oxygen saturation and (D) total suspended solids (TSS) for station TC1 in Turkey Creek for monthly surveys from April- December 2015. Numbers on A, B and C refer to the number of month when profile was obtained……………………………………………………………………………….……….3-25 Figure 3.13. Vertical profiles for (A) salinity, (B) temperature, (C) % oxygen saturation and (D) total suspended solids (TSS) for station TC5 in Turkey Creek for monthly surveys from April- December 2015. Numbers on A, B and C refer to the number of month when profile was obtained………………………………………………………………………………………..3-26 Figure 3.14. Vertical profiles for (A) dissolved ammonium, (B) dissolved nitrate + nitrite, (C) total dissolved nitrogen and (D) dissolved organic carbon (DOC) for station TC1 in Turkey Creek for nine monthly surveys from April-December 2015………………………………….3-28 Figure 3.15. Vertical profiles for (A) dissolved ammonium, (B) dissolved nitrate + nitrite, (C) total dissolved nitrogen and (D) dissolved organic carbon (DOC) for station TC5 in Turkey Creek for nine monthly surveys from April-December 2015………………………………….3-29 3- Figure 3.16. Vertical profiles for (A) dissolved phosphate (PO4 ) and (B) total dissolved phosphorus at station TC1, and (C) dissolved phosphate and (D) total dissolved phosphorus at station TC5 (with scale change for x-axis) in Turkey Creek for nine monthly surveys from April- December 2015 ………………………………………………………………………………3-31 Figure 3.17. (A) Turbidity (in nephelometric turbidity units, NTU) versus total suspended solids TSS), (B) Turbidity versus TSS from Trefry et al. (2007) for samples from the Indian River Lagoon System (MB = Melbourne, VB = Vero Beach, BR = Banana River Lagoon, TB = Turnbull Creek area, ML = Mosquito Lagoon). Solid lines and equation are from linear regression analysis, dashed lines show 95% prediction interval. Anomalous data points are identified by water depth, location and month during 2015...... 3-32

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List of Figures (Continued)

Figure 3.18. Vertical profiles for (A) total suspended solids (TSS), (B) particulate organic carbon (POC), (C) particulate organic nitrogen (PON), and (D) total particulate phosphorus at station TC1 in Turkey Creek for nine monthly surveys from April-December 2015...... 3-34 Figure 3.19. Vertical profiles for (A) total suspended solids (TSS), (B) particulate organic carbon (POC), (C) particulate organic nitrogen (PON), and (D) total particulate phosphorus at station TC5 in Turkey Creek for nine monthly surveys from April-December 2015...... 3-35 Figure 3.20. (A) Particulate organic carbon (POC) versus aluminum (Al), (B) total particulate nitrogen versus POC, (C) total particulate phosphorus versus POC and (D) total particulate iron versus total particulate Al. Solid lines and equation are from linear regression analysis, dashed lines show 95% prediction interval. Anomalous data points are identified by water depth, location and month during 2015……………………………………………………………….3-36 Figure 3.21. Pie diagram showing the percentages of the different chemical forms of nitrogen in the waters of Turkey Creek and the adjacent Indian River Lagoon…………………...………3-39 Figure 3.22. Pie diagram showing the percentages of the different chemical forms of phosphorus in the waters of Turkey Creek and the adjacent Indian River Lagoon...... 3-40 Figure 4.1 Conceptual diagram of the bottom water column based upon previous observations and mathematical models (modified after Mehta, Lee and Li, 1994 and reproduced from B Bostater and Rotkiske, 2015) ...... 4.3

Figure 4.2 Fluxes in metric tons per day (mT day-1) at locations indicate the fluid mud movement for pre-dredge, during dredging and post dredging conditions obtained from a recent Florida Inland Navigation District dredging project. Results for transect 4 (upper right) indicates muck movement reduction (MMR) occurred during the study near Sebastian Florida during 2015...... 4.8

Figure 4.3 Pre-dredge fluidized muck and mud sample locations during 2015. Stations were selected using stratified random sampling in order to insure stations were located (1) west of the railroad bridge, (2) in the main bay of Turkey Creek and (3) near the mouth of Turkey Creek. Georeferenced satellite image courtesy Digital Globe ...... 4.9

Figure 4.4 Pre-dredge sonde sediment mass flux station results extrapolated in terms of lbs. m-2 day-1 for 2015 Turkey Creek samples using the east (blue) and west (red) directional horizontal sondes...... 4-11

Figure 4.5 Measured sonde fluid mud mass flux results extrapolated in terms of lbs. m-2 day-1 for 2015 Turkey Creek pre-dredging stations from the red upwelling (resuspension) and

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List of Figures (Continued) downwelling (depositional) sondes. Values shown represent combined surface and bottom probe measurements...... 4-11

Figure 4.6 Conceptual bottom lutocline and nepheloid layer (0.5 m deep) through which fluid mud and muck movement was measured using the sondes. The horizontal and vertical sonde measurements allow one to extrapolate the mass movement or flux density – lbs. per year moving through an idealized bottom cross-sectional area (vertical slice) as depicted above… 4-12

Figure 4.7 Subsurface image (left) from station TCP2 at ≈10 cm above the bottom. Large colloidal assemblages and flocs were identifiable in the water just outside the horizontal sonde. The right image shows flocs and colloidal aggregates in clear near bottom water collected at station TCB1 ...... 4-13

Figure 4.8 Stations TB1, TB2 and TB3 station locations in Turkey Creek west of the railroad bridge...... 4-14

Figure 4.9 Station horizontal sonde (westward facing) triplicate (n=3) deployment results for percent loss on ignition (% LOI) and eastward facing sondes with single deployments at each station (n=1) were pooled giving N=3. The above data represent % LOI results from a total of 12 horizontal sondes simultaneously deployed during October 1-3, 2015...... 4-15

Figure 4.10 Sonde downstream flux direct measurements (g m-2 day-1) based upon triplicate deployment results for Turkey Creek stations TCB1 and TCB2, west of the railroad bridge. These results suggest the sonde method has good reproducibility based upon the simultaneous deployments yielding a coefficient of variability of 0.125 and 0.147...... 4-16

Figure 4.11 Percent LOI results at station TCB1 from horizontal and vertical sondes...... 4-17

Figure 4.12 Station TCP1 % loss on ignition (LOI) results from the depositional and resuspension sondes described by Bostater & Yang, 2014. Organic matter was greater in the bottom depositional sonde. The % loss on ignition data is used in this report to estimate particulate nutrients captured within the fluid mud using the results of Trefry, 2015...... 4-17

Figure 4.13 Station TCP1 % loss on ignition (LOI) results from the horizontal sondes described developed by Bostater & Yang, 2014. The results depicted above indicates the percent organic

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List of Figures (Continued) matter was different based upon the directional movement of the fluid mud, with the greatest organic matter content from material moving from the north and indicated by the size of the blue triangle...... 4-18

Figure 4.14 Schematic showing results of combining sonde depositional % LOI and Trefry, 2015 nutrient relations for estimating nutrient deposition per hectare for use in water quality model calibrations...... 4-19

Figure 4.15 Discharge time series during the October, 2015 deployment period...... 4-19

Figure 4.16 Clear bottom layer water at station TCB1 (right) collected with the sludge judge. Subsurface nephelometric layers are visible as wavelike features in the image (left) below the secchi depth in the fixed station acoustic echogram image (left) taken from a 0.0-165 sec time recording. The water depth was ~1.9 m and water temperature 28.6 oC. ... 4-20

Figure 4.17 Station TCB1 floc size (cross-sectional area) determined from image analysis using the methods reported by Bostater and Rotkiske, 2015. Median floc sizes were near 30 mm2. These dominate sizes are in the 2,000-3,000 micron range and are the equivalent size range of US Screen Mesh numbers ≈ 6-12...... 4-21

Figure 4.18 Multispectral 3 channel image (lower) and the zoomed multispectral sub-image (top) of colloidal aggregates and flocs taken from a multispectral 3 channel image (lower). Measurements were obtained at station TCB1 in Turkey Creek west of the railroad bridge (N 28.032076, W -80.682458338) on October 3, 2015 using the methods described in Bostater and Yang, 2014, and Bostater and Rotkiske, 2015...... 4-22

Figure 4.19 Sonde total non-directional moving particulates in the lutocline (dry weight) extrapolated to grams m2 day-1 from (1) stations at the mouth and just outside of Palm Bay (n=52), (2) stations west of the railroad bridge (n=52), and (3) stations east of US1 within Palm Bay (n=54)...... 4-23

Figure 4.20 Gridded and color contoured map of the moving (total non-directional particulate organic matter) dry weight flux (g m-2 day-1) in the lower 0.5-meter water column based upon horizontal and vertical sonde data from stations east of US 1 and at the mouth of Turkey Creek are shown. A spatial grid of ~25 m2 is overlaid on gridded image. Subsurface characterization

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List of Figures (Continued) is based upon utilizing Bayesian kriging power semivariogram methods (Nobre and Sykes, 1992)...... 4-24

Figure 4.21 Georeferenced map of estimated total particulate matter (dry weight) flux (g m-2 day-1) moving in the lower 0.5 meter water column based upon horizontal and vertical sonde data from stations east of US 1 and at the mouth of Turkey Creek. A spatial grid of ~25 m2 is overlaid on the 6.2 m2 gridded image. Subsurface characterization utilizes Bayesian kriging power semivariogram methods (Nobre and Sykes, 1992)...... 4-25

Figure 4.22 Georeferenced map of estimated particulate phosphorus flux (g m-2 day-1) moving in the lower 0.5 meter water column based upon total horizontal and vertical sonde data from stations east of US 1 and at the mouth of Turkey Creek. A spatial grid of ~25 m2 is overlaid on the 6.2 m2 gridded image. Subsurface characterization utilizes Bayesian kriging power semivariogram methods (Nobre and Sykes, 1992)...... 4-25

Figure 4.23 Gridded and contoured georeferenced map of estimated particulate nitrogen flux (g m-2 day-1) moving in the lower 0.5-m water column based upon total horizontal and vertical sonde data from stations east of US 1 and at the mouth of Turkey Creek. A spatial grid of ~25 m2 is overlaid on the 6.2 m2 gridded image. Subsurface characterization utilizes Bayesian kriging power semivariogram methods (Nobre and Sykes, 1992)...... 4-26

Figure 4.24 Gridded and contoured georeferenced map of estimated particulate organic carbon flux (g m-2 day-1) moving in the lower 0.5-m water column based upon total horizontal and vertical sonde data from stations east of US 1 and at the mouth of Turkey Creek. A spatial grid of ~25 m2 is overlaid on the 6.2 m2 gridded image. Subsurface characterization utilizes Bayesian kriging power semivariogram methods (Nobre and Sykes, 1992)...... 4-26

Figure 4.25 A high spatial resolution airborne multispectral (3 band) image of Turkey Creek with a GSD of approximately 6 cm2. The image has been processed for detecting subsurface bottom features and bottom reflectance using the methods published and described by Bostater, 2006, 2008, 2012. Only the lower left area of the water surface is influenced by sun glint. The zoomed inset in the upper left shows the detail in the high spatial resolution airborne imagery …………………………………………………………………………………………………4-27

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List of Figures (Continued)

Figure 4.5.1 Operation of the sondes or probes is based upon perturbation theory that indicates the sondes automatically perform a time and spatial averaging collection method to collect moving fluidized mud. The method allows one to capture particulate matter fluctuations where turbulence, water wave effects, variations in flux fluctuations due to mean river flow, fluctuating concentrations and velocities dominate instantaneous measurement systems in use today (from Bostater & Rotkiske, 2016)...... 4-30

Figure 4.5.2 Map of stations for Task 4 and as described in the above table...... 4-33

Figure 4.5.3 Method for calculating the moving fluid mud flux density for the horizontal and vertical sondes. The cross-sectional area for the vertical sondes is 20.261 cm2 and the cross- sectional area for the horizontal sondes is 81.073 cm2 (based upon ANSI approved NEIKO Model 01412A Digital Caliper, 0.02 mm Accuracy, 0.01 Digital Resolution)...... 4-34

Figure 4.5.4 Muck depth (m) variability at stations TCB1 thru TCB3 during April and October Deployments. Total observations n=12 (n=4 at each station). The October pooled mean precision using the coefficient of variation (CV x 100) was 89% using the sludge judge or push pole technique. This measure of reliability is considered typical of this method for measuring muck depth...... 4-37

Figure 4.5.5 Example of a field sampling log sheet used to record sonde deployments at each station and any field related information...... 4-40

Figure 5.1. Flow diagram for the EFDC hydrodynamic and transport model. Drifter dye, and near filed plume calculations are driven by subroutines within the main body of the EFDC model...5-3

Figure 5 2. Flowchart for the water quality module of HEM3D...... 5-4

Figure 5.3. Extent of the model grid in two panels oriented north-south. Model grid contains about 9,400 computational water cells and 5 vertical layers, each representing 20% of the water column. Mode boundaries correspond with available time series of water level and salinity data...... 5-9

Figure 5.4. Model grid in the Turkey Creek area...... 5-10

Figure 5.5. Long term IRL monitoring stations for freshwater, water level, salinity and water temperature...... 5-11

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List of Figures (Continued)

Figure 5.6. Water level time series applied in file to force north and south model boundaries. Annual highstand of sea level seen in October 1999 is included in model calibration (see Figure 5.12)...... 5-13

Figure 5.7. Surface salinity time series applied in model, along with near- bottom salinity data to force north and south model boundaries ...... 5-13

Figure 5.8. Location of water quality monitoring station maintained by the SJRWMD...... 5-15

Figure 5.9. Boundaries of the watershed model sub-basin links to the IRL model. Barrier Island watersheds are not included...... 5-16

Figure 5.10. Example of total nitrogen and total phosphorus inputs to the EFDC/HEM3D model from the SWIL watershed model from 1994 to 2010. Inputs are received from the Turkey Creek sub-basin ...... 5-17

Figure 5.11. Sediment diagenesis schematic...... 5-18

Figure 5.12. Model and measured water level comparison in the Sebastian River...... 5-20

Figure 5 13. Comparison of measured and model salinity at the mouth of Sebastian River. .... 5-21

Figure 5.14. Comparison of measured and predicted dissolved oxygen values for a 1999 calibration period...... 5-23

Figure 5.15. Five month time series of predicted total N and total P concentrations under pre- dredge conditions from a numerical observation station about 5 km south of Turkey Creek entrance ...... 5-25

Figure 5.16. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located in the entrance of Turkey Creek ...... 5-26

Figure 5.17. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located about 4 km north of Turkey Creek entrance...... 5-27

Figure 5.18. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located about 4 km south of Turkey Creek entrance...... 5-28

Figure 5.19. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located about 10 km south of Turkey Creek entrance...... 5-28

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List of Tables

Table 1.1 IRLRI Environmental Muck Dredging Research 2015 Monthly/QuarterlyMeetings…………………..………………………………………...1-3 Table 1.2 Indian River Lagoon Research Institute (IRLRI) Muck Research Related Presentations ...... 1-4 Table 2.1 Infaunal species list ...... 2-22 Table 2.2 Fish catch summary ...... 2-29 Table 3.1 Data quality objectives for the proposed study...... 3-11 Table 3.2 Water depths (n = 199) and muck thicknesses (n = 199) for Turkey Creek...... 3-14 Table 3.3 Concentrations of selected elements in surface sediments from Turkey Creek. Station locations shown on Figure 3.5. Shading identifies samples that fit the 1987 definition of muck……………………………………………………………………………………...……3-16 Table 3.4 Grain size distribution and aluminum content for surface sediments from Turkey Creek and the adjacent Indian River Lagoon. Station locations on Figure 3.6. Shading identifies samples that fit the 1989 definition of muck…………………………………………………..3-17 Table 3.5 Summary of 2015 data from (A) continuous profiles obtained using a YSI Sonde 6600 and (B) 135 discrete water samples (15/month). The text in parentheses for maximum (max) and minimum (min) values gives station identification, water depth and month sampled ...... 3-23 Table 3.6 Concentrations of the various forms of nitrogen in the water column of Turkey Creek and the adjacent IRL. Dates and locations of maxima and minima are shown in [ ]. Units are µM and {mg N/L}………………………………………………………………………………….3-38 Table 3.7 Percentages of the various forms of nitrogen in the waters of Turkey Creek and the adjacent IRL...... 3-38 Table 3.8 Percentages of the various forms of dissolved nitrogen in the waters of Turkey Creek and the adjacent IRL ...... 3-39 Table 3.9 Concentrations of the various forms of phosphorus in the water column of Turkey Creek and the adjacent IRL...... 3-41 Table 3.10 Percentages of the various forms of phosphorus in the waters of Turkey Creek and the adjacent IRL….………………………………………………………………………………..3-41 Table 3.11 Percentages of the various forms of dissolved phosphorus in the waters of Turkey Creek and the adjacent IRL...... 3-41

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List of Tables (Continued)

Table 4.1 Published definitions of fluid mud and muck collected within the sondes (reproduced from Bostater and Rotkiske, 2016)……………………………………………………………...4-5

Table 4.2 Comparison between the May-October (May/October) water “depth” and “muck” depths at stations west of the railroad bridge in Turkey Creek. Muck depths and water depths measured with a sludge judge indicates observed muck depths changed between May and October sampling dates indicating muck depth changes………………………………………………...4-20

Table 4.5.1 Description of samples collected during 2015 at each station……………….…….4-32

Table 4.5.2 Station locations (latitude longitude decimal degrees), station ID and region…….4-33

Table 4.5.3 Triplicate deployment results at three stations for % loss of ignition (% organic matter) within sonde moving fluid mud………………………………………………………..4-38

Table 4.5.4 Triplicate deployment results from two stations for moving horizontal sonde fluid mud flux measurements in g m -2 day-1of total organic particulate nitrogen. …………………4-38

Table 4.5.5 Triplicate deployment results from two stations for horizontal sonde moving fluid mud flux dry weight measurements in g m -2 day-1……………………………………………4-38

Table 4.5.6 Pooled station duplicate deployment results (TCB1 and TCB2) for vertical sonde particulate flux precision estimates………………..…………………………………………..4-39

Table 5.1 List of water quality variables that can be calculated by EFDC/HEM3D model...... 5-4

Table 5.2 Hydrodynamic and transport input files ...... 5-12

Table 5.3 Summary of Major EFDC/HEM3D Water Quality Input Files ...... 5-14

Table 5.4 Sediment model state variables ...... 5-18

Table 5.5 Statistics of model-data comparisons in the lower Sebastian River for calibration and verification ...... 5-22

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Acknowledgements

Funds for these investigations were provided by the Florida legislature as part of DEP Grant Agreement No. S0714 – Brevard County Muck Dredging.

Valuable guidance and feedback throughout the yearlong investigation was given by Matt Culver, Virginia Barker and Mike Mcgarry of the Brevard County Natural Resources Management Department. Other inputs throughout the year from external reviewers and comments on the draft final reports also improved the project and the final report. Those external reviewers included Robert Virnstein, Joel Steward and Charles Jacoby.

Advice on field and laboratory measurements and historic data were provided by Lori Morris and Robert Chamberlain, St. Johns River Water Management District, Sherry Reed, Smithsonian Marine Station, and Richard Paperno, Florida Fish and Wildlife Conservation Commission.

Many Florida Institute of Technology students contributed to the success of this project in the field and in the laboratory. Graduate students working on the project were Maria Angelica Zamora-Duran, Anthony Cox, Daniel Hope, James King, Anthony Cianciotto, Jacob Rennert, Jennifer Richards and Taylor Oney. Undergraduate students working on the project were Mollie Wightman, Kelsie Ebeling-Whited, Kenneth Millar, Catherine Lamboy and numerous students in fisheries and other biology classes.

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Chapter 1 Muck Dredging Research Project Management

John G. Windsor Florida Institute of Technology, Melbourne, FL 32901

1.1 Summary

Five interdisciplinary projects developed by the Indian River Lagoon Research Institute (IRLRI) at Florida Institute of Technology are coordinated through the muck dredging research project management office: (1) Muck Dredging Research Project Management, (2) Biological Responses to Muck Removal, (3) The Efficiency of Muck Removal from Indian River Lagoon and Water Quality after Muck Removal, (4) Movement Measurements of Muck and Fluidized Mud at Dredge Sites, and (5) A Hydrologic and Water Quality Model for Management and Forecasting within Brevard County Waters of Indian River Lagoon. Regular meetings of the Florida Institute of Technology Environmental Muck Dredging (FIT-EMD) research principal investigators with representatives from Brevard County Natural Resource Management Department, Florida Department of Environmental Protection and St. Johns River Water Management District, and a team of external scientific consultants facilitate the exchange of scientific findings among all the investigators and optimize the outcomes of these research investigations. In addition, the project management office engages the public about muck dredging research through presentations open to the public and through social media.

1.2 Introduction In order to address serious water quality issues associated with muck sediment in the Indian River Lagoon, the Florida Legislature in the 2014 session directed one million dollars to the Florida Institute of Technology through Brevard County to investigate the effects of environmental muck dredging in the Indian River Lagoon (IRL). A collaborative, interdisciplinary effort, through the Indian River Lagoon Research Institute (IRLRI), developed the following projects to help better manage future muck removal efforts throughout the state.

1. Muck Dredging Research Project Management Project Management coordinates effective communications of research plans and results between principal investigators, Brevard County Department of Natural Resources Management, other agencies, external reviewers and the public.

2. Biological Responses to Muck Removal In preparation for planned environmental muck dredging, this project monitors three essential measures of lagoon ecosystem health through the following studies: seagrass surveys; benthic infauna surveys; and fish surveys. When dredging occurs, the surveys conducted this year will serve as the baseline for comparison for determining whether these key populations recover or improve after the muck has been removed.

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3. The Efficiency of Muck Removal from the IRL and Water Quality after Muck Removal. This project is addresses both the muck removal and water quality issues by (1) determining the muck removal efficiency using high-resolution measurements and (2) making in situ measurements and collecting water samples for chemical analysis to help assess the impact of muck removal on water quality.

4. Movement Measurements of Muck and Fluidized Mud at Dredge Sites. This project (1) measures in-situ movement (horizontal and vertical) of fluid mud and muck at transects and stations in Turkey Creek west of the railroad bridge, east of US 1 in Turkey Creek at 2 locations in the IR and (2) collects data at the stations and transects using newly developed fluid mud and muck sondes or probes. The data will help assess the impacts of muck removal on lagoon water quality and will provide new methods and information to assist in setting future dredging priorities.

5. Hydrologic and Water Quality Model for Management and Forecasting within Brevard County Waters of the IRL. A coupled hydrodynamic-water quality model of the IRL develops a tool for understanding the ecology, maintaining water quality goals, and forecasting the potential benefits of management strategies. The approximate model domain extends between north Mosquito Lagoon and Vero Beach.

In the Chapters 2 through 5, the principal investigators report on environmental conditions before dredging at Turkey Creek in Palm Bay, Florida. Each Chapter is intended to stand alone.

1.3 Approach

Each of the five projects is coordinated through the project management office. Regular meetings of the Florida Institute of Technology Environmental Muck Dredging (FIT-EMD) research principal investigators facilitate the exchange of scientific findings among all the investigators. Results of field and lab work as well as logistics discussions are shared with all interested parties. The project management office assembles and distributes written monthly, quarterly and final project reports. The project management office also keeps Brevard County Natural Resources Management Department staff up to date on muck dredging research findings by (1) sending email updates, (2) holding monthly scientific roundtable discussions with interested (IRL) agencies and organizations, (3) conducting quarterly scientific presentations and project review meetings, and (4) obtaining and incorporating peer review by external scientists. In addition, the project office engages the public about muck dredging research through presentations open to the public and through social media applications.

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1.4 Results

Project design and research updates have been discussed at monthly and quarterly meetings throughout the year. Representatives from Brevard County Natural Resources Management Department, FDEP, SJRWMD and Harbor Branch Oceanographic Institute at FAU all receive the monthly and quarterly reports through the FIT-EMD mailing list. Anyone who has requested regular updates has been added to the list. Monthly and quarterly meeting dates are shown in Table 1.1.

Table 1.1 IRLRI Environmental Muck Dredging Research 2015 Monthly/Quarterly Meetings  March 16, 2015 – Discussion of results, logistics and sampling strategies  April 20, 2015 – Discussion of results, logistics and sampling strategies  May 18, 2015* – Quarterly Meeting at Florida Tech; After updates from each PI, discussion items included alteration to some of the field sampling locations, transplantation of seagrass, how deep the dredging should be in Turkey Creek and dredging permit progress.  July 20, 2015 – Discussion of results, logistics and sampling strategies  August 10, 2015* – Quarterly at Brevard County Department of Natural Resource Management; The FIT-EMD team regular August monthly meeting was conducted at the Brevard County Natural Resources Management Department office in Viera. Suggestions from IRLRI PIs for continuation and new projects were entertained during the meeting. On hand were County staff, FIT administrative staff, and external reviewers.  September 14, 2015 – Since the August meeting discussions continued among those attending the review meeting to provide feedback to all those who proposed projects. Scopes of Work (SOWs) were developed for each project proposed based on the feedback received from the review process. These SOWs were submitted to the County for additional review and comment. As a result of this repetitive, interactive process, all of the new and continuation projects are ready to begin.  November 9, 2015* – Quarterly Meeting at Florida Tech; Discussion focused on initiation of dredging, logistics and continuation of current projects and initiation of new projects.  December 14, 2015 – Discussion of results, logistics and sampling strategies during dredging.  February 1, 2016* – Combined January/February meeting. Discussion of results, logistics and sampling strategies during dredging. *indicates quarterly meeting

External scientific review is important for the ongoing work. At least three independent reviewers have offered comments throughout the year, including reviews of current research direction as well as future proposed efforts. An external review panel was assembled and 1-3

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In addition to coordinating the research efforts, reaching out to the community is important to explain the impacts of IRL muck and the potential benefits associated with muck removal in the overall context of IRL restoration. Highlights of outreach efforts undertaken by the PIs on this project are summarized in Table 1.2 below. Twitter and Facebook continue to be used to describe some muck basics, issues associated with muck, the ongoing research relevant to muck, the need for muck removal and the progress on muck removal and public presentations by the FIT Environmental Muck Dredging Research Team. Follow @IRLMuck #IRLMuck.

Table 1.2 Indian River Lagoon Research Institute (IRLRI) Muck Research Related Presentations

 March 13, 2015 – John Windsor gave a presentation to the Senior Life Expo describing better management of Indian River Lagoon resources, which included describing muck and removing muck.  April 2, 2015 – Muck removal from the Indian River Lagoon was the title of a talk by Dr. John Trefry presented to the Space Coast Progressive Alliance.  April 22, 2015 – Dr. Trefry gave muck removal presentation before the Indian River Lagoon Counties Collaborative meeting at the Indian River County Commission chambers.  May 18, 2015 – John Windsor gave a short presentation on the necessity of muck removal research to a group of concerned citizens attending “An Estuary Affair” at Florida Institute of Technology.  May 22, 2015 – Muck removal investigations were part of the IRLRI (Indian River Lagoon Research Institute) presentation by Dr. Robert Weaver at the Indian River Lagoon Counties Collaborative.  May 26, 2015 – John Windsor appeared briefly at the Brevard County Commission meeting to let them know that the FIT-EMD was working on the muck removal investigations.  July 7, 2015 – John Windsor discussed muck removal at the Eau Gallie Rotary Club meeting.  August 21, 2015 – Dredging research in Indian River County was the subject of a presentation by Robert Weaver to the Florida Inland Navigation District Board.  August 25, 2015 – John Windsor provided public comments to the Melbourne City Council on an issue regarding the disposal of muck sediment from the Eau Gallie River.  September 26/27, 2015 – IRLRI PIs attended the first annual IRLRI Tech Con in Melbourne, Florida. Much discussion at the conference was focused on impacts of muck and strategies for muck removal and management. FIT-EMD PIs will be assisting in the organization of next year’s meeting. Drs. Weaver and Zarillo gave talks describing muck removal and modeling the effects of muck removal on Indian River Lagoon.

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Table 1.2 Indian River Lagoon Research Institute (IRLRI) Muck Research Related Presentations (Cont’d)

 October 13, 2015 – Dr. Trefry spoke to the Board of County Commissioners, Indian River County, about impact of muck on Indian River Lagoon and the necessity for its removal from the Lagoon. He also emphasized preventing muck from entering the Indian River Lagoon.  October 20, 2015 – Dr. Trefry spoke to the Exchange Club of South Brevard about impact of muck on Indian River Lagoon and the necessity for its removal from the Lagoon. He also emphasized preventing muck from entering the Indian River Lagoon.  November 6, 2015 – Dr Zarillo discussed his Indian River Lagoon modelling efforts at the ShORE2015 Conference in Daytona Beach, Florida. Several other IRLRI PIs attended.  February 10, 2016 – Drs. Johnson and Trefry presented muck related research as part of the Algal Bloom Initiative meeting at Harbor Branch Oceanographic Institute in Fort Pierce  February 11, 2016 – Dr. Austin Fox presented a paper at the Indian River Lagoon Symposium 2016 entitled Identifying Controls on Fluxes of Dissolved Nitrogen from Sediments in the Northern Indian River Lagoon by Austin L. Fox, John H. Trefry, Robert P. Trocine, and Stacey L. Fox, Florida Institute of Technology, Melbourne, FL.  February 11, 2016 – Daniel Hope presented a paper at the Indian River Lagoon Symposium 2016 entitled Organic Sediment Characteristics and Benthic Infaunal Diversity in the Indian River Lagoon by Daniel Hope, Tony Cox, Angelica Zamora-Duran, and Kevin B. Johnson, Florida Institute of Technology, Melbourne, FL  February 11, 2016 – Angelica Zamora-Duran presented a paper at the Indian River Lagoon Symposium 2016 entitled Benthic Foraminifera as Bioindicators of Environmental Conditions in the Indian River Lagoon by Angelica Zamora-Duran, Anthony Cox, Daniel Hope, and Kevin B. Johnson, Florida Institute of Technology, Melbourne, FL  February 24, 2016 – Dr. Austin Fox presented a paper at Oceans 2016 in New Orleans entitled Physical, chemical and biological controls of nutrient fluxes from fine-grained, organic-rich sediments in the Indian River Lagoon, Florida by Austin L. Fox, John H. Trefry, Robert P. Trocine, Stacey L. Fox, Florida Institute of Technology, Melbourne, FL

An important element that should be captured from all the research and dredging activities that have occurred to date and planned over the next few years is “What Lessons Did We Learn?” An interdisciplinary team of Coastal Zone Management and Environmental Resource Management graduate students recently began to develop an Indian River Lagoon Muck Management Manual. The lessons learned from the IRL muck dredging experience will be of value to coastal environmental muck dredging projects not just for the entire IRL, but also throughout the state of Florida.

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Chapter 2 Biological Responses to Muck Removal

Kevin Johnson and Jonathan Shenker Florida Institute of Technology, Melbourne, FL 32901

2.1 Summary

Muck at the bottom of the Indian River Lagoon (IRL) creates an inhospitable environment for plants and animals. In addition, indirect effects of muck, such as nutrient flux into overlying waters can fuel algal blooms, creating stress on pelagic and benthic organisms. As muck is removed from the IRL through environmental dredging efforts, it is essential that we document post-dredge vs pre-dredge ecological conditions, confirming whether or not selected benthic and pelagic components of the IRL system are enhanced. This report details the monitoring of key biological populations (seagrasses, drift algae, invertebrate infauna, and fishes) in Turkey Creek (City of Palm Bay, Brevard County) and the adjacent IRL targeted for environmental muck dredging, as well as in control areas in the IRL for comparison.

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anchovy catches reflect the patchy distribution of the schools and their movement into and out of Turkey Creek. Demersal juvenile fishes were dominated by mojarras (Eucinostomus spp. and Diapterus spp.; 3.2% of the total catch), and the important commercial/recreational fisheries family Sciaenidae (including silver perch, red drum, Atlantic croaker, spot, sea trout and kingfish; 2.3% of the total catch). The temporal patterns of abundance of these juveniles are influenced by the temporal and spatial patterns in adult spawning behavior. These baseline data will enable us, once dredging in Turkey Creek has occurred, to make comparisons in biological populations and communities before and after environmental muck dredging.

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2.2 Introduction

In association with Brevard County’s dredging plans, we have monitored biological populations in a region targeted for environmental muck dredging. This monitoring has included measurements of environmental conditions, especially the sediments, and population ecology of seagrasses, drift algae, infauna, and fishes of the Indian River Lagoon. Muck removal is intended to improve IRL ecosystems, providing an opportunity for stressed populations to rebound. Measuring critical ecosystems near dredging sites, before the dredging actually occurs, prepares us for [future] during- and post-dredging comparisons, which will allow us to evaluate the success of muck removal. Sampling areas proximal to planned dredging sites, as well as away from dredge sites at thriving areas, allows interpretations to be more conclusive on the driving forces behind observed changes.

Objective

• Pre-dredging assessment of seagrasses, benthic fauna and fishes near dredging sites, contrasted with away or control sites.

Seagrasses and Drift Algae

Seagrasses are key indicators of lagoon health, promote biodiversity, and form critical habitat that serves as a nursery for juvenile fish populations (Virnstein and Morris 1996, Morris et al. 2001). They thrive in medium to low nutrient conditions in clear shallow water. Drift algae, while a natural part of estuarine and lagoon systems, tend to thrive with higher nutrients. Abundant drift algae can smother and/or shade seagrasses. Thus, the relative abundance of these two types of primary producers can indicate much about the relative condition of the ecosystem and possible eutrophic nitrification. In Turkey Creek (Palm Bay), sediments in the deeper areas are muck, while sediments in the shallower waters are not purely muck, but still contain high Fine-Grained Organic-Rich Sediments (FGORS) (see Trefry and Trocine 2011 for muck and FGORS definitions based upon sediment characteristics and chemistry). Sparse seagrasses (Halodule wrightii) occur in this body, and it is common for drift algae (Gracilaria spp.) to accumulate and rest on top of seagrass. Sediment conditions and the apparent competition of algae with struggling seagrass make it a good test system to see if removal of FGORS can improve the benthic conditions sufficiently for measurable improved seagrass growth. Because infaunal (Wong and Dowd 2015) and fish (Hori et al. 2009) communities are known to thrive in seagrasses, there is also ample potential for indirect effects.

Infauna

Macro- and microinvertebrates in estuarine sediments are food for benthic foraging fish and their burrows and movements serve to aerate the sediments (Gonzalez-Ortiz et al. 2014). These organisms are perhaps the most directly affected by the conditions of sediments, and are presumed to be negatively impacted by high organic content and unable to live in muck. However, the effects of 2-3

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FGORS and muck on infaunal populations and communities have not been empirically tested or demonstrated in the literature.

A common and potentially important infaunal organism in Turkey Creek is the foraminiferan Ammonia parkinsoniana. Ammonia was the first genus assigned to Foraminifera in 1772 (Holzmann 2000) and since then has been a focus of research due to global distribution and variable morphology, especially since morphology has been shown to vary due to pollution (Boltovskoy et al. 1991; Alve, 1995; Colburn 1998; Frontalini 2015) Over 46 species, subspecies and varieties have been described (Holzmann 2000). Ammonia are common in benthic, nearshore environments, with Ammonia parkinsoniana being found in shallower waters (Jorissen 1988). Ammonia parkinsoniana tolerate wide ranges of temperature and salinity, and hypoxic conditions (Cushman, 1970; Karlsen et al. 2000). Foraminifera have been used as environmental bioindicators of water quality and pollution in estuarine ecosystems (Ishman et al. 1997; Gapotchenko et al. 2000; Karlsen et al. 2000; Alves Martins et al. 2015), although one has to be cautious about interpreting the implications of their presence if patches frequently surge in abundance and disappear (Buzas et al. 2015). Foraminifera can be used as a tool for assessing and monitoring the ecosystems due to their distribution, abundance, short generation times, reliable fossil record, and environmental sensitivity (Schönfeld et al. 2012). Indices have been proposed whereby resource managers can monitor environmental conditions and recovery by watching foraminiferan assemblages (Sen Gupta et al. 1996; Hallock et al. 2003). In addition to monitoring efforts, paleoecological data from fossilized foraminiferan tests provide invaluable temporal perspectives to ecologists and restoration planners (Willard and Cronin2007). Due to their tolerances to organic sediments, it is anticipated that A. parkinsoniana’s abundance and distribution may be responsive to the removal of FGORS sediments and the subsequent reduction of the ammonia, hypoxia, and hydrogen sulfide associated with those sediments.

Fishes

Fishes constitute one of the most valuable and visible components of the Indian River Lagoon ecosystem. The highly diverse ichthyofauna of the IRL includes many species that support recreational fisheries, with other species filling important ecological roles. The life history strategy of IRL species reflect several basic patterns. Some species spend their entire lives from egg through adult stage within the lagoon. Others spawn near the inlets or offshore, producing planktonic larvae that ultimately settle as juveniles in various habitats in the lagoon. Regardless of the reproductive strategy used, most species rely on juvenile nursery habitats within the lagoon. Human impacts on these juvenile habitats are considered among the greatest potential factors that can influence the population structure and dynamics of the species.

In the 1990s, the State of Florida began a very intensive survey of juvenile fishes throughout the IRL and many other estuarine habitats around Florida. The Fisheries Independent Monitoring Program (FIM) developed standardized sampling protocols that are utilized in a broad sampling program

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through the IRL and other targeted estuaries (FWCC 2014). Data collected by this decades-long fisheries survey can be used to identify natural variations in juvenile abundance and distribution, and to assess potential anthropogenic impacts on fish populations (e.g., Tremain and Adams 1995; Paperno and Mille 2001; Paperno et al. 2006).

The FIM program uses a stratified random sampling procedure to establish sampling sites throughout the entire Indian River Lagoon region. The researchers expend a tremendous amount of effort on the sampling, and their data have helped define the temporal and spatial patterns of habitat utilization of lagoon species, as well as quantifying short-term and interannual variations in abundance. However, the lagoon is so vast that annual sampling density in any given region, such as Turkey Creek, is generally low, precluding fine-scale assessment of individual habitats or events.

The FIM sampling strategy, at a far smaller spatial and temporal scale, was employed for this project to generate a far more detailed picture of the temporal and spatial distribution of fishes within and adjacent to the planned muck removal site within the mouth of Turkey Creek (“Palm Bay”). These data can be compared with the wider FIM database to evaluate site specific attributes of the fish fauna within Turkey Creek and adjacent IRL habitats.

The adult fishes that utilize the Turkey Creek habitats are not vulnerable to capture using the FIM juvenile fish sampling techniques. Interviews with anglers fishing in Turkey Creek, and our personal experiences, have identified a number of adult fishery species, including sheepshead (resident on dock pilings and oyster/rock piles), jacks and red drum (highly mobile schooling species), tarpon and (juvenile) bull sharks (generally solitary mobile predators). The mobile predators tend to follow schools of prey, including anchovies, mullet, and herrings, so their utilization of the Turkey Creek habitats can be highly variable.

2.3 Approach (Including referenced methods)

Biological monitoring was conducted in the region near the mouth, but within Turkey Creek (“Palm Bay”), where environmental muck dredging will soon occur. In addition, biological monitoring was conducted at various sites away from the dredging for comparison with the biological work adjacent to the anticipated dredging.

Sampling Sites and Methods - Seagrasses and Drift Algae

Four 100-m transects were surveyed perpendicular to the shoreline at 3 major sites: within Turkey Creek (TC), in the Indian River Lagoon (IRL) near Turkey Creek (TCL), and in the IRL near Crane Creek (CCL) (Figure 2.1). Quadrats were laid down every 10 m along the transect lines, and seagrasses and drift algae were scored according to standard methods (Virnstein & Morris 1996, Morris et al. 2001). Measurements included seagrass visual estimate % cover (estimated coverage

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Technology Annual Report, July 2016 upon imagining the seagrass crowded into corner of quadrat at a high density), seagrass % coverage or occurrence (proportion of 100 quadrat sub-squares having at least 1 blade of seagrass), seagrass density (# of shoots per area), seagrass canopy height (the length of blade from sediment to tip), drift algae % occurrence (the proportion of 100 quadrat sub-squares having any drift algae), drift algae biomass estimate (estimated coverage upon imagining drift algae crowded into corner of quadrat), and drift algae canopy height (Virnstein & Morris 1996, Morris et al. 2001). Sampling was conducted monthly from May-December, 2015. Seagrass and algal abundances were plotted as means ± SE. Where appropriate, statistical comparisons were made via ANOVA.

Sampling Sites and Methods – Benthic Fauna

Sediment grabs for infaunal analysis were collected at the 50-m mark along all seagrass transects described above (Figure 2.1) via Petite Ponar Grab (n=3 per transect). In addition, 4 sites were selected in the heart of the most concentrated muck sediments, including 2 sites in Turkey Creek muck (TCM, n=3 each) and 2 sites in Crane Creek muck (CCM, n=3 each) (see Figure 2.1). Sampling and identification of infauna were conducted consistent with the methods of ongoing benthic studies of the IRL (Mason 1998, Cooksey and Hyland 2007, Tunberg et al. 2008b). Abundances, diversity, and richness of fauna were tested for correlations with sediment parameters, including % organic content (dry weight), % water content by weight, % silt/clay content (dry weight), and score on a subjective hydrogen sulfide odor index. Where appropriate, statistical analyses included ANOVA for spatial comparisons on a given day, ANOVA for temporal comparisons for a given site, NMDS community analysis with posthoc ANOSIM, and regression correlation analysis comparing biological data to corresponding sediment data.

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Figure 2.1. Primary study sites, including A. Turkey Creek (“Palm Bay”) and locations of seagrass transects TC-1-TC-4. B. Comparison study site in the Indian River Lagoon near the mouth of Turkey Creek (TCL) and locations of TCL transects (TCL-1-TCL-4). C. Comparison study site in the Indian River Lagoon near the mouth of Crane Creek (CCL) and locations of CCL transects (CCL-1-CCL-4). Yellow dots indicate locations of infaunal sampling (triplicates of monthly sampling at each marked location). D. Fish sampling sites along the western shore of Turkey Creek (F-W), north shore of Turkey Creek (F-N) and outside of the mouth of Turkey Creek (F-O). Transect lengths (red lines) are 100 m. Seine sites (yellow boxes) are 9 by 15.5 m.

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Sampling Sites and Methods – Fishes

Fish samples were collected monthly from April 2015 through December 2015 from a series of 4 sites along the western shore of Turkey Creek (F-W in Figure 2.1D), 4 sites along the north shore of Turkey Creek (F-N), and 2 sites outside the mouth of Turkey Creek (F-O). All sampling was done following standardized Fisheries Independent Monitoring Program (FIM) seining protocols (FWCC 2012). Fishes were collected with a 21.3-m long center bag seine x 1.8 m deep, and constructed of 3.2-mm knotless nylon Delta mesh. A 15.5-m rope was tied to the towing poles at each end of the seine, and 9 m-long ropes were attached to poles placed in the sediment at the beginning of each tow.

These guide ropes ensured that the seine sampled a standardized area of 140 m2 (9 m by 15.5 m). Sample locations within each of the 3 regions were haphazardly selected by water depth and substrate. Within each Turkey Creek site, 2 samples were collected by towing the seine along the shore at an approximate starting depth of 50-75 cm. Two samples were taken further from shore, generally at a starting depth of about 1 m. The location of the deeper tows were restricted by the beginning of increasingly soft sediments, defined as when the seine personnel sank knee deep (about 30 cm) in muck, and could no longer effectively drag the net. Regions F-W and F-N were the only areas within Turkey Creek where the seine net could be effectively deployed.

Following completion of a seine tow, fishes were identified to the lowest practical taxonomic level and counted. A sample splitter was occasionally used to estimate numbers of very large catches of anchovies and several other species. Standard lengths of up to 25 specimens of each taxon were recorded. Voucher specimens were placed on ice for laboratory identification, if necessary.

Data analysis began by converting abundance data to density data (number of fish/100 m2). Monthly mean densities were then calculated for inside Turkey Creek (generally 8 samples) and outside Turkey Creek (2 samples). For each dominant species, a 2-way ANOVA was used to test for temporal and spatial patterns in their utilization of the habitats in and adjacent to Turkey Creek. To determine if different sized or life stages of fishes have different patterns of habitat utilization, length- frequency data for total catch of each dominant taxon were compared between the Turkey Creek and data provided by the Florida Fish and Wildlife Conservation Commission’s Fisheries Independent Monitoring Program (FIM) from habitats within 1 km north and south of the mouth of Turkey Creek. A Kolmogorov-Smirnov (K-S) test was used to compare length-frequency distributions.

To examine potential community level patterns in fish abundance and distributions, fish population data from Turkey Creek samples collected from May to December 2015 were compared to data from samples taken from 1991 to 2014 by the FIM program from sites within 1 km north and south of Turkey Creek. An analysis of similarity (ANOSIM), using a Bray-Curtis similarity index, was used to determine the similarity of the fish community within the embayment of Turkey Creek to the community of fishes along the open Indian River Lagoon shoreline.

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Quality Assurance and Quality Control

Personnel and equipment – To ensure consistency of approach, execution, and interpretation, the same personnel have been employed continually since the launch of the project. With regard to their training, they have been trained by personnel at the St. Johns River Water Management District (SJRWMD) and the Smithsonian Marine Station (SMS) for the seagrass/drift algae surveys and benthic infauna sampling, respectively. Staff at SJRWMD and SMS have been sampling these biological communities in Indian River Lagoon ecosystems for at least two decades. In addition to basic knowledge of how to sample, it is desirable to be able to compare our results to data generated by the sampling programs of these other agencies. Therefore, we have made an effort to have methods, equipment, and techniques mirror those used in other sampling occurring in the lagoon. This includes the same quadrat methods employed by SJRWMD for seagrass and drift algae sampling and the same Petite Ponar Grab methods utilized by SMS for benthic infauna collection. Instrumentation and the intended data collection activities are itemized on a process checklist, which is consulted during monthly preparations for data collection. Team member Angelica Zamora-Duran is the quality assurance assistant for field deployments and data collection.

Water quality – salinity, temperature, dissolved oxygen (DO), depth, and clarity of the water in the regions of seagrass and infaunal sampling are collected with appropriate instruments. Salinity, temperature, and DO are collected with a YSI meter, which is calibrated against a laboratory refractometer, thermometer, and DO meter, respectively, at least once per month.

Seagrass and drift algae surveys – The identification of seagrasses and drift algae has been carefully checked against all species occurring in the area and then verified by other seagrass experts. By utilizing the quadrat method recommended for local use by employees of the SJRWMD (Morris et al., 2001; Virnstein & Morris 1996), we are ensuring robust and replicate observations at each single point along a transect. Our personnel calibrate their transect scoring via a joint quadrat evaluation at the onset of each sampling day. Regarding regional seagrass transect replication, our methods exceed those employed by SJRWMD, with whom our personnel have trained and methods mirrored. For instance, SJRWMD generally uses a single transect to evaluate seagrasses in a particular area, whereas we use four, all within a few hundred meters of one another. The greater spatial resolution is intended to better characterize a focused area, namely the targeted dredge site and the control sites. Multiple observations to characterize an area is an important part of quality assurance, preventing a few anomalous observations from driving misleading interpretations.

Benthic infauna – The depth of sediment penetration and consistency of sediment volume collection by the Petite Ponar grab (PPG) have been tested and compared in sediments of different grain size and quality. This has enabled us to confidently calculate the numbers of infaunal organisms per area and volume of sediment. In addition, we have sampled with sediment cores deeper than the PPG penetrates to gain knowledge of the frequency with which organisms are beyond the reach of the

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PPG, and under which conditions. Horizontal 1-cm slices of test cores confirmed that most organisms are being captured in grabs that penetrate only 3 cm, especially in mucky and intermediate sediments. Sandy sediments can have a relative few organisms beyond the reach of the PPG and this should be kept in mind when interpreting PPG data and making comparisons between the sediments. Species identifications have been confirmed by experts in the respective taxonomic fields. Additional species verification is planned via DNA analysis with comparisons against next generation sequencing databases. When species are unconfirmed, they are maintained under an alias (e.g., Polychaete A) that is universally used by all technicians until the identity is certain. Type specimens of both confirmed and undetermined species are maintained in labeled Eppendorf vials and preserved in 4% formalin. Our replication to represent an infauna collection site is identical to that utilized by SMS (n=3). Proper replication is essential for quality assurance because it prevents a single anomalous observation from driving misleading interpretations. Infaunal methodology intended to ensure accuracy and reliability of data is consistent with methods described in Mason (1998), Cooksey and Hyland (2007), and Tunberg et al. (2008b).

Sediment collection – sediment grabs for chemical and physical analysis are collected from the same locations, and with the same replication and methodology, as infauna collection. Regarding water content determination, the decanting of water in the field is consistent and removes obviously separate water from around the sample, after which the sediment is placed in a Ziploc bag. The entire sample is then used for water content comparison. To determine the combined silt-clay content, the sample is washed through 63 micron mesh, and the dry weights determined and compared. The qualitative determination of hydrogen sulfide content is a subjective test and we therefore have 3 personnel independently smell the sediment samples and make a sulfide score determination without knowing how others have scored the samples.

Fishes – Sampling effort was standardized using FWCC (2014) protocols for the FIM Program with a 21.3-m center bag seine. Measured lines were used to maintain the seine mouth width at 15.5 m and the tow length at 9 m, covering an area of 140 m2. Sample processing also followed the FIM protocols for subsampling (if necessary) using a volumetric sample splitter for counting and measuring a subsample of abundant fishes (typically anchovies and mojarras). The subsample split factor was then applied to the subsample count to produce an estimate of the total number of fishes in the catch.

Fish identifications were conducted in the field by at least four trained personnel, who all had to agree with the species identification. If unanimity of identification was not achieved, representative specimens were examined in the field and the laboratory using published field guides (Lippson and Moran 1974; Ray and Robins 1999; Hoese and Moore 2008). All data were recorded and checked in the field on waterproof data sheets.

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Data Handling – Data spreadsheets are checked by two personnel for correctness at the close of each data entry session. Spreadsheet files are backed up monthly, with fish data stored on a Google Drive site.

2.4 Results and Discussion

2.4.1. Seagrasses and Drift Algae

Depths of seagrass transects were variable with tide and wind conditions. Nearshore transects were between 40-70 cm in depth within 20 m of shore and increased to 95-135 cm depth at 50 m from shore, and then maintained a relatively level depth out to the 100-m quadrat. Seagrasses, where they occur, show a declining trend through our sampling period, based upon % cover (Figure 2.2), visual percent cover (Figure 2.3), and shoot counts (Figure 2.4). Seagrasses are less abundant in the slightly deeper water towards the end of transects (90 and 100-m markers). These data also show the consistent lack of occurrence of seagrasses within Turkey Creek throughout the year (Figures 2.2A, 2.3A, and 2.4A), while the IRL sites have seagrass and the opportunity for seasonal patterns to be observed. It should be noted that struggling sparse patches of Halodule wrightii were observed in Turkey Creek during the high growth season (late spring/early summer), but were not abundant enough to occur in random transects and quadrats. Canopy height, equivalent to shoot length, is more unpredictable, but generally peaked in May for the IRL near Turkey Creek (TCL), subsequently declining in the ensuing 2015 seasons (Figure 2.5C). In the IRL near Crane Creek (CCL) canopy height was even more inconsistent, with some locations peaking later in the year (August, Figure 2.5B).

Drift algae were evaluated along the same transects as those designed for seagrasses. Unlike seagrasses, drift algae were abundant in Turkey Creek along all transects throughout much of the year. Drift algae largely disappeared from the Indian River Lagoon sites in the fall (October, Figure 2.6 B&C), and were entirely absent from all sites in the winter (December, Figure 2.6 A-C). Drift algal biomass patterns (Figure 2.7) were similar to percent cover (Figure 2.6). Drift algal canopy heights were greater in the spring (May), often 10-15 cm, and decreased to mostly under 5 cm in the summer (August) and fall (October) before disappearing (Figure 2.8). During the peak of the year, Turkey Creek (TC) drift algal canopy heights (Figure 2.8A) often range from 10-16 cm, forming a strong shade blanket over any aspirant shoots of seagrass in the area. This shading is occurring during what would otherwise be the primary seagrass growth season.

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Figure 2.2. Seagrass mean % cover (% occurrence) at A) Turkey Creek (no seagrasses observed in random transects) B) The IRL near Crane Creek, and C) The IRL near Turkey Creek. Selected months represent seasons. Note the different scales. Error bars = ±1SE.

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Figure 2.3. Seagrass mean visual estimate % cover at A) Turkey Creek (no seagrasses observed in random transects) B) The IRL near Crane Creek, and C) The IRL near Turkey Creek. Selected months represent seasons. Note the different scales. Error bars = ±1SE.

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Figure 2.4. Seagrass mean shoot counts at A) Turkey Creek (no seagrasses observed in random transects) B) The IRL near Crane Creek, and C) The IRL near Turkey Creek. Selected months represent seasons. Note the different scales. Error bars = ±1SE.

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Figure 2.5. Seagrass mean canopy height at A) Turkey Creek (no seagrasses observed in random transects) B) The IRL near Crane Creek, and C) The IRL near Turkey Creek. Selected months represent seasons. Error bars = ±1SE.

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Figure 2.6. Drift algae mean percent cover at A) Turkey Creek B) The IRL near Crane Creek, and C) The IRL near Turkey Creek. Selected months represent seasons. Error bars = ±1SE.

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Figure 2.7. Drift algae mean percent biomass at A) Turkey Creek B) The IRL near Crane Creek, and C) The IRL near Turkey Creek. Selected months represent seasons. Note different scales. Error bars = ±1SE.

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Figure 2.8. Drift algae mean canopy height at A) Turkey Creek B) The IRL near Crane Creek, and C) The IRL near Turkey Creek. Selected months represent seasons. Error bars = ±1SE.

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Sediments and Infauna

Sediments were evaluated with regard to the primary features that indicate the degree of fine-grained, organic-rich sediments (FGORS) in the samples. FGORS indicator parameters are % water content (by weight) (Figure 2.9), % silt/clay content (dry weight) (Figure 2.10), % organic content (dry weight) (Figure 2.11), and a subjective odor (H2S) score (Figure 2.12). Sediments with very high FGORS components are what the popular press refers to as “muck”. In all cases, selected “muck” sites in Turkey Creek (TCM, Figure 2.1A) and Crane Creek (CCM) (Figure 2.1C), were confirmed to have very high FGORS scores (Figures 2.9-2.12) relative to the sites with seagrass transects. Turkey Creek (TC) had intermediate scores for all muck indicators, while the lagoon sites (TCL and CCL) had the lowest scores (Figures 2.9-2.12). Muck, lagoon, and intermediate stations having statistically distinct FGORS characteristics is worth noting because it is a gradient in these organic sediments that we hypothesize may drive species diversity and abundances.

Figure 2.9. Mean % water content of sediments by weight. Sites from nearest to furthest from the dredging site are Turkey Creek (TC), Turkey Creek Muck (TCM), the Indian River Lagoon near Turkey Creek (TCL), Crane Creek Muck (CCM), and the Indian River Lagoon near Crane Creek (CCL). Muck sites (TCM, CCM) have statistically higher water content relative to other stations. Turkey Creek (TC) has a statistically distinct intermediate water content relative to other stations. Error bars are ±1SE.

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Figure 2.10. Mean % silt+clay content of sediments (dry weight). Sites include Turkey Creek (TC), Turkey Creek Muck (TCM), the Indian River Lagoon near Turkey Creek (TCL), Crane Creek Muck (CCM), and the Indian River Lagoon near Crane Creek (CCL). Muck sites (TCM, CCM) have statistically higher silt+clay relative to non-muck stations. Turkey Creek (TC) has a statistically distinct intermediate silt+clay relative to muck and lagoon stations. Error bars are ±1SE.

Figure 2.11. Mean % organic matter content of sediments (dry weight). Sites include Turkey Creek (TC), Turkey Creek Muck (TCM), the Indian River Lagoon near Turkey Creek (TCL), Crane Creek Muck (CCM), and the Indian River Lagoon near Crane Creek (CCL). Muck sites (TCM, CCM) have statistically higher organic content relative to all other stations. Turkey Creek (TC) has a statistically distinct intermediate organic content relative to muck and lagoon stations. Error bars are ±1SE.

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Figure 2.12. Mean subjective sulfur odor (smell intensity index). Sites include Turkey Creek (TC), Turkey Creek Muck (TCM), the Indian River Lagoon near Turkey Creek (TCL), Crane Creek Muck (CCM), and the Indian River Lagoon near Crane Creek (CCL). Muck sites (TCM, CCM) have statistically higher odor index relative to other stations. Turkey Creek (TC) has a statistically distinct intermediate odor index relative to muck and lagoon stations. Error bars are ±1SE.

Infaunal species were less diverse in intermediate FGORS sediments (TC) and almost zero in confirmed muck sediments (CCM and TCM) (Table 2.1 and Figure 2.13). Muck sites (TCM and CCM) usually supported no species, but a single sampling event did find some animals in two grabs. Species richness (Figure 2.14) followed similar patterns. Species included foraminiferans, gastropod mollusks, bivalve mollusks, decapod crustaceans, gammarid amphipods, caprellid amphipods, polychaete annelids, ostracod crustaceans, tanaid crustaceans, nematodes and others. A cumulative list of all species found at respective sites is given in Table 2.1 (n=12 grabs at each major site monthly throughout the year).

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Table 2.1. Cumulative infaunal species list for all sites: Turkey Creek (TC), Turkey Creek Muck (TCM), Indian River Lagoon near Turkey Creek (TCL), Crane Creek Muck (CCM), and Indian River Lagoon near Crane Creek (CCL). An asterisk indicates abundant species. Of the non-muck sites, CCL had the greatest, TC had the lowest, and TCL was intermediate in abundances. High abundance thresholds warranting special notation in this table were different for the three sites. Abundant organisms noted below (*) exceeded 150, 300, and 500 individuals m-2 for TC, TCL, and CCL, respectively. TC TCL CCL CCM TCM S=46 S=59 S=57 S=1 S=4

Acteocina atrata Acteocina atrata Acteocina atrata Ammonia parkinsoniana Acteocina canaliculata *Acteocina canaliculata *Acteocina canaliculata *Acteocina canaliculata Ammonia parkinsoniana *Ammonia Alpheus heterochaelis *Ammonia parkinsoniana parkinsoniana Clam A *Ammonia parkinsoniana Amygdalum papyrium Amygdalum papyrium Parastarte triquetra *Amygdalum papyrium Angulus versicolor Angulus versicolor Annelid H *Annelid H *Annelid H

Annelid I Annelid I Astyris lunata Astyris lunata Astyris lunata Bulla occidentalis Bulla occidentalis Bulla occidentalis Callinectes sapidus Callinectes sapidus Capitella capitata Capitella capitata Capitella capitata Clam A Clam A Clam A Clam B *Clam B Clam B Clam F Clam F Cumacean A Crab B Crab B

Cyrtopleura costata Crepidula atrasolea *Cumacean A *Diopatra sp A *Cumacean A Cyrtopleura costata Eurypanopeus depressus Cynoscion nebulosus Diopatra sp A *Eusirus cuspidatus Cyrtopleura costata *Eusirus cuspidatus *Gammarid Amphipod C *Diopatra sp A Gammarid Amphipod C Eurypanopeus Gammarid Amphipod D depressus Gammarid Amphipod D Gammarid Amphipod F Eusirus cuspidatus *Gammarid Amphipod F Gammarid Amphipod G Gammarid Amphipod C Gammarid Amphipod G

Hemipholis elongata Gammarid Amphipod D Hargeria rapax Mercenaria mercenaria Gammarid Amphipod G Hemipholis elongata Nematode A Hargeria rapax Mercenaria mercenaria *Nereis A Hemipholis elongata Metacaprella sp A Odostomia laevigata Limulus polyphemus Nematode A Ostracod B Mercenaria mercenaria *Nereis A

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Table 2.1. Continued. TC TCL CCL CCM TCM *Parastarte triquetra Metacaprella sp A Odostomia laevigata Pectinaria gouldii Nematode A *Parastarte triquetra *Peratocytheridea setipunctata *Nereis A Pectinaria gouldii *Peratocytheridea Phascolion cryptus Odostomia laevigata setipunctata Polychaete D Ostracod B Periglypta listeri Polychaete L *Parastarte triquetra Phascolion cryptus Polychaete M Pectinaria gouldii Polychaete A *Peratocytheridea Polychaete N setipunctata Polychaete C Polychaete O Phascolion cryptus Polychaete D Polychaete Q Polychaete D Polychaete H *Polychaete T Polychaete H Polychaete K Shrimp A *Polychaete L Polychaete L Sipuncula B Polychaete M Polychaete M Snail F *Polychaete N Polychaete N Snail H Polychaete O Polychaete O Snail K Polychaete P Polychaete P Tanaid A Polychaete R Polychaete Q *Tanaid B Polychaete S Polychaete R *Polychaete T Polychaete S Polychaete U *Polychaete T Shrimp B Shrimp A Sipuncula B Snail F Snail C Snail H Snail F Snail J Snail H Snail K Snail J Snail M Snail K *Tanaid A Snail M *Tanaid B *Tanaid A Tanaid C Tanaid B Tanaid C

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Figure 2.13. Mean infaunal biodiversity throughout the year at five sites. Sites include Turkey Creek (TC), Turkey Creek Muck (TCM), the Indian River Lagoon near Turkey Creek (TCL), Crane Creek Muck (CCM), and the Indian River Lagoon near Crane Creek (CCL). Error bars are ±1SE.

Figure 2.14. Mean infaunal species richness throughout the year at five sites. Sites include Turkey Creek (TC), Turkey Creek Muck (TCM), the Indian River Lagoon near Turkey Creek (TCL), Crane Creek Muck (CCM), and the Indian River Lagoon near Crane Creek (CCL). Error bars are ±1SE.

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Species richness and diversity showed correlations with sediment characteristics. Log relationships were shown where lower FGORS scores (i.e., relatively low organic, silt/clay, or water content) correlated with high diversity and richness. Figure 2.15 shows correlations for biological infaunal data collected in October, November, and December, paired with sediment samples collected concurrently. Relationships were similar when regressed against all FGORS parameters. The relationships are here demonstrated with species richness against % Organic Matter (Figure 2.15A) and % Silt Clay content (Figure 2.15B).

Figure 2.15. A. [log] infaunal species richness vs. [log] % sediment organic matter (dry weight). B. [log] species richness vs. [log] % silt/clay (dry weight).

Community analysis reveals that species abundance is more distinctive temporally (changes through the seasons, represented by selected months) at sandier (low FGORS) sites (Figure 2.16B, R=0.42, p=0.001) compared to a similar analysis done with high FGORS sites (Figure 2.16A), R=0.12, p=0.001).

Figure 2.16. NMDS infaunal community analysis using abundance of species (Bray Curtis Distance Analysis). A. FGORS sites. B. Sandy sites.

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Focusing on Ammonia parkinsoniana, a foraminiferan potentially useful as an indicator species because of its tolerance of high organic low quality sediments (Ishman et al. 1997; Gapotchenko et al. 2000; Karlsen et al. 2000; Alves Martins et al. 2015), abundances within Turkey creek (TC) were greatest in May 2015, with abundances dropping off except along one transect in July (Figure 2.17). A. parkinsoniana was ephemeral or episodic, nearly disappearing in June 2015, then resurging before disappearing completely in September. This is likely a phenomenon known in foraminiferans as “pulsing patches” (Buzas et al. 2015).

Figure 2.17. Abundance of foraminifera (Ammonia parkinsoniana) in Turkey Creek from May- September, 2015. TC1-TC4 are individual transects. Disparate letters within a month’s sampling indicate statistically significant differences.

Ammonia parkinsoniana abundance, when they are consistently present and reasonably abundant (see May and June, Figure 2.17) correlates with FGORS characteristics. Using [log] % Silt/Clay from aforementioned fall sediment samples as a representative parameter, [log] A. parkinsoniana abundance showed the best correlation in May, when it was most abundant and consistently present across transects (Figure 2.18A).

Figure 2.18. Foraminiferan (Ammonia parkinsoniana) abundance in Turkey Creek as a function of % silt/clay during A) May and B) July, the most abundant months of A. parkinsoniana occurrence in 2015.

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2.4.2. Fishes

A total of 129,873 fishes from 56 taxa were collected from April through December 2015 (Table 2.2). The fishes captured in the seine were dominated by small pelagic schooling species and demersal juvenile fishes. Pelagic anchovies (Anchoa spp.) comprised 92.2% of the entire seine catch, indicating the numerical dominance of these fishes in the Turkey Creek region of the IRL ecosystem. Juvenile mojarras (Eucinostomus spp. and Diapterus spp.; 3.2% of the catch) dominated the demersal fishes. Demersal juveniles of the commercially important fisheries family Sciaenidae (including silver perch, red drum, Atlantic croaker, spot, sea trout and kingfish) comprised 2.3% of the total catch. Temporal and spatial patterns of distribution of dominant and important taxa are discussed below.

Abundance and size data for individual taxa reflect seasonal recruitment patterns and spatial distributions that vary in response to fish behavior and environmental influences. Distribution, density and size data collected for the dominant species during 2015 are presented below. To put fish data from the 2015 sampling in Turkey Creek into a broader temporal and spatial context, size distribution data from selected fish taxa within Turkey Creek in 2015 were compared with FIM data collected from in and around Turkey Creek from 1991 to 2014. FIM data were also used to compare total fish community structure observed in 2015 in Turkey Creek with the community structure of adjacent habitats collected over previous decades.

Anchovies: Although these small pelagic schooling fishes (primarily bay anchovy, Anchoa mitchilli) greatly dominated the total catch, the schooling and highly mobile behavior of these fishes resulted in extremely patchy temporal and spatial distributions (Figure 2.19). The presence of schools of anchovies were generally immediately visible at the onset of sampling, and larger predatory fishes (such as jacks and tarpon) were observed feeding in the vicinity. Schools frequently moved in and out of the Turkey Creek habitat. It was common to catch them in several seine hauls on Day 1 of a 2 day sampling period within any month and find them essentially absent on Day 2 of the sampling period, reflecting their ability to move quickly in and out of Turkey Creek.

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Figure 2.19. Mean (+/- S.D.) density (number/100 m2) of anchovies (Anchoa spp.) captured monthly from inside Turkey Creek (typically 8 samples per month) and just north of the mouth of Turkey Creek (2 samples per month).

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Table 2.2 Total catch of fishes collected by seine net from stations inside and adjacent to the mouth of Turkey Creek, FL.

FISH Scientific Name Common Name Apr May Jun Jul Aug Sep Oct Nov Dec TOTAL Anchoa spp. Anchovies 1,045 57,406 46 12,005 16,149 104 889 520 31,599 119,763 Eucinostomus spp. Mojarras 381 433 193 297 294 27 38 109 433 2,205 Bairdiella chrysoura Silver perch 595 246 158 915 91 0 10 5 0 2,020 Diapterus spp. Irish pompano/mojarra 36 12 37 447 914 59 51 208 181 1,945 Opisthonema oglinum Atlantic thread herring 0 1,310 0 0 0 0 0 0 0 1,310 Sciaenops ocellatus Red drum 0 0 0 0 1 0 10 1 383 395 Micropogonias undulatus Atlantic croaker 189 9 4 1 15 0 0 59 0 277 Brevoortia spp. Menhadens 187 69 3 0 0 0 0 0 1 260 Lagodon rhomboides Pinfish 154 51 4 38 6 0 0 0 0 253 Mugil curema White mullet 0 0 0 2 1 1 71 117 23 215 Menidia spp. Silversides 0 0 1 14 126 0 30 4 6 181 Menticirrhus americanus Southern Kingfish 0 1 1 0 1 0 3 89 63 158 Harengula spp. Sardines/pilchards 51 9 0 1 28 0 0 0 48 137 Cynoscion spp. Sea trout 0 29 0 8 5 0 3 77 3 125 Mugil spp. Mullet 105 0 1 1 0 0 0 0 0 107 Archosargus probatocephalus Sheepshead 2 14 7 47 3 0 3 1 0 77 Strongylura spp. Needlefish 0 3 37 6 9 8 3 3 3 72 Oligoplites saurus Leatherjacket 0 19 5 16 4 5 5 5 0 59 Leiostomus xanthurus Spot 0 53 0 0 0 0 0 0 0 53 Trinectes maculatus Hogchoker 2 2 5 4 11 0 0 1 10 35 Gobiosoma robustum Code goby 1 6 1 4 3 0 8 0 3 26 Carangidae spp. Jacks 0 5 0 0 0 0 18 0 0 23 Gobiidae spp. Gobies 0 0 11 9 2 0 0 0 0 22 Syngnathus scovelli Gulf pipefish 4 9 1 1 1 0 0 0 0 16 Ariopsis felis Hardhead catfish 1 4 0 1 1 0 5 0 0 12 Elops saurus Ladyfish 0 8 0 1 0 0 0 0 1 10 Dasyatis sabina Atlantic stingray 2 1 0 1 5 0 0 0 0 9

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Table 2.2 Total catch of fishes collected by seine net from stations inside and adjacent to the mouth of Turkey Creek, FL (continued).

Scientific Name Common Name Apr May Jun Jul Aug Sep Oct Nov Dec TOTAL Lutjanus griseus Gray snapper 0 1 0 1 2 1 3 1 0 9 Chaetodipterus faber Spadefish 6 2 0 0 0 0 0 0 0 8 Citharichthys spilopterus Bay whiff 8 0 0 0 0 0 0 0 0 8 Fundulus spp. Killifish 0 0 7 0 0 0 0 0 0 7 Microgobius gulosus Clown goby 3 3 1 0 0 0 0 0 0 7 Sphyraena barracuda Great barracuda 0 0 1 3 1 2 0 0 0 7 Syngnathus louisianae Chain pipefish 0 4 1 0 0 0 0 0 0 5 Haemulon spp. Grunts 4 0 0 0 0 0 0 0 0 4 Paralichthys spp. Flounder 0 3 0 1 0 0 0 0 0 4 Caranx hippos Crevalle jack 0 1 0 0 0 0 1 1 0 3 Hypleurochilus pseudoaequipinnis Oyster blenny 0 0 0 2 1 0 0 0 0 3 Mugil cephalus Striped mullet 1 0 0 0 1 0 1 0 0 3 Orthopristis chrysoptera Pigfish 0 2 1 0 0 0 0 0 0 3 Paralichthys lethostigma Southern flounder 3 0 0 0 0 0 0 0 0 3 Pogonias cromis Black drum 0 0 1 1 0 0 0 0 1 3 Sphoeroides testudineus Checkered pufferfish 0 0 2 0 0 0 0 0 1 3 Achirus lineatus Lined Sole 0 0 0 1 1 0 0 0 0 2 Cynoglossidae spp. Tonguefish 0 0 0 0 2 0 0 0 0 2 Sciaenidae spp. drum juveniles 2 0 0 0 0 0 0 0 0 2 Trachinotus carolinus Florida pompano 0 0 0 0 0 0 0 2 0 2 Sheepshead/sea Archosargus sp. bream hybrid 0 0 0 1 0 0 0 0 0 1 Centropomus spp. Snook 0 0 1 0 0 0 0 0 0 1 Chilomycterus shoepfi Striped burrfish 0 0 0 0 0 0 0 0 1 1 Chloroscombrus chrysurus Atlantic bumper 0 1 0 0 0 0 0 0 0 1 Eugerres plumieri Striped mojarra 0 1 0 0 0 0 0 0 0 1 Gobiosoma bosc Naked goby 1 0 0 0 0 0 0 0 0 1

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Table 2.2 Total catch of fishes collected by seine net from stations inside and adjacent to the mouth of Turkey Creek, FL (continued).

Scientific Name Common Name Apr May Jun Jul Aug Sep Oct Nov Dec TOTAL Gymnura micrura Smooth butterfly ray 0 1 0 0 0 0 0 0 0 1 Hyporhamphus meeki False silver halfbeak 0 1 0 0 0 0 0 0 0 1 Sphoeroides nephelus Southern pufferfish 0 0 0 0 0 1 0 0 0 1 TOTAL 2,783 59,719 530 13,829 17,679 212 1,155 1,206 32,760 129,873

INVERTEBRATES Callinectes sapidus Blue crab 8 2 0 7 6 0 3 1 1 28 Penaeidae spp. Shrimp 0 23 1 5 1 2 42 13 7 94 TOTAL 8 25 1 12 7 2 45 14 8 122

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Mojarras: Two groups of juvenile mojarras were the most abundant of the demersal species found in Turkey Creek habitats, and were widely dispersed among all the sampling regions. Small juvenile Eucinostomus spp. and Diapterus spp. are difficult to identify to species, so the fishes were generally identified to the genus level. These groups of mojarras had different seasonal patterns within Turkey Creek, but no significant differences in densities among the sampled habitats (Figure 2.20). Eucinostomus spp. were abundant throughout the spring and summer, but experienced a significant decline (ANOVA, p<0.05) in abundance through the fall. In contrast, Diapterus spp. increased in abundance in two summer months, followed by a drop in the fall.

Figure 2.20. Mean (+/- S.D.) density (number/100 m2) of mojarras: top) Eucinostomus spp. and bottom) Diapterus spp. captured monthly from inside Turkey Creek (typically 8 samples per month) and just north of the mouth of Turkey Creek (2 samples per month; April not sampled). Lines with different letters indicate temporal periods with significantly different fish densities (ANOVA, p<0.05).

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The occurrence of juvenile Eucinostomus spp. throughout the study was composed of fishes ranging from 15-90 mm SL. The collection of small juveniles during most months suggests a protracted spawning season for these fishes, while Diapterus spp. (15-90 mm) were common primarily during the summer. Adults of these species range from 150-350 mm SL, and are presumed to spawn in offshore or inlet habitats (Kerschner et al. 1985).

Both genera exhibited major declines in abundance beginning in September. These declines may have been due to seasonal or age-related migration out of the Turkey Creek habitat. However, intense rainfall in September resulted in very high flow of freshwater from the Turkey Creek watershed (USGS, 2016; Figure 2.21), reducing salinities at the sampling stations from 20-25 ppt during the summer months to values less than 10 ppt in September.

Figure 2.21. Water discharge at the USGS gage station number 02250030 on Turkey Creek, located approximately 3 km upstream of the mouth of the creek into the Indian River Lagoon (USGS 2016).

A further evaluation of how similar the mojarra populations at the sampling stations inside and adjacent to Turkey Creek can be developed by comparing these data with the data collected by the FIM program. The FIM sampling protocol divides the Indian River Lagoon into 1 km2 blocks (Figure 2.22), then uses a random stratified sampling process to select precise locations for sampling on each day. FWCC graciously provided us with their entire Indian River Lagoon database. Grid 364 includes the Turkey Creek habitats sampled by the

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360

364 368

Figure 2.22. Sampling grid established by the Florida Fish and Wildlife Conservation Commission’s Fisheries Independent Monitoring Program for selecting seine sampling stations. Grid 364 includes the embayment at the mouth of Turkey Creek. FIM Fisheries data collected from Grid 364, Grid 360 (north of Turkey Creek) and Grid 368 (south of Turkey Creek) were used for comparison with data collected by this sampling program.

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A comparison of the length-frequency data collected by this project and by the extensive FIM sampling effort shows that the length distribution of Eucinostomus spp. collected within Turkey Creek by our project in 2015 is not significantly different from that collected by the FIM sampling within Turkey Creek during 1991-2014 (Grid 364), north of Turkey Creek (Grid 360) and south of Turkey Creek (Grid 368) (Kolmogorov-Smirnov [KS] Test, p>0.05). Data presented in Figure 2.23 are the total abundance of all fish in each length class collected by the total sampling effort; the K-S test evaluates potential differences in relative frequencies of size classes among the sampling groups.

Figure 2.23. Length-frequency distributions of mojarras: A) Eucinostomus spp. and B) Diapterus spp. collected by this program (yellow bars) and FIM (Grid 364/Turkey Creek = red bars; Grid 360 north of Turkey Creek = green bars; Grid 368 south of Turkey Creek = blue bars).

These data indicate that the mojarra species are widely dispersed across the western side of the IRL around Turkey Creek, and that Turkey Creek itself is not a unique habitat for the taxa. However, these species are important prey species for larger predators, including many of the recreationally-important fishes. Factors affecting their abundance and growth may thus impact the prey base for predators. The mojarras typically inhabit sandy habitats, often

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extending into adjacent seagrass beds. They have a highly protrusible mouth that enables them to capture small epibenthic and infaunal prey such as polychaete worms, amphipods, cumaceans, and small bivalves (Kerschner et al. 1985; Mota et al. 1995). Given this ability to feed in sandy substrates, they are well adapted to thrive in the narrow band of sand and shallow mud around the periphery of the mouth of Turkey Creek. Analyses of the stomach contents of mojarras collected during 2015 is presently underway, which will permit comparison of their feeding with the prey base available in muck and sand habitats in the region. Preliminary evidence presented in this report suggests that muck habitats contain very few, if any, suitable prey taxa. We hypothesize that the removal of muck from Turkey Creek will expose sandy substrates that can develop a community of benthic species and ultimately provide resources to support a larger abundance of juvenile mojarras. This increase in mojarra population size may, in turn, enhance the prey base for the larger predatory fishes (e.g. sea trout, red drum, tarpon, juvenile bull sharks) that utilize Turkey Creek.

Silver Perch: This small member of the drum family was the third most abundant species collected during 2015 sampling. It was significantly more abundant in Turkey Creek and the adjacent sampling site outside Turkey Creek from April through July, but was almost entirely absent in the latter half of the year (Figure 2.25; 2 way ANOVA, p<0.05). Densities within Palm Bay were generally highest in the northern stations (F-N), where the substrate included patches of oyster shell and Gracilaria drift algae, as compared to the western shoreline stations (F-W) which were characterized by sand/muck substrate.

Silver perch spawn in early spring in estuarine channels, with larvae and early juveniles generally occurring in mesohaline seagrass, sand and oyster habitats and adults moving into higher salinity regions (Rooker et al. 1998; Hanke et al. 2013). Length frequency and seasonal abundance data from the Turkey Creek region provide some support for this trend, with the smaller juveniles found within Turkey Creek in spring (Figure 2.24 and 2.25), and larger specimens taken in the IRL north and south of the mouth of Turkey Creek. A further analysis of FIM data that encompasses a wider range of lagoon habitats may provide a more conclusive analysis of this potential trend.

Analysis of the feeding habits of silver perch in the northern Gulf of Mexico show that primary prey items of small juveniles include epibenthic crustaceans such as mysid shrimp and amphipods (Waggy et al. 2007). These prey are often associated with physical structures such as oyster shell, seagrass and drift algae. Stomach contents of fish collected by this program are presently being analyzed for comparison with benthic infauna/epifaunal samples still being processed. The presence of muck in much of Turkey Creek presumably limits the abundance of these organisms. The removal of muck should expose more suitable substrate for these prey taxa, providing a greater food base to support silver perch and other demersal fishes. 2-36

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Figure 2.24. Mean (+/- S.D.) density (number/100 m2) of silver perch (Bairdiella chrysoura) captured monthly from inside Turkey Creek (typically 8 samples per month) and just north of the mouth of Turkey Creek (2 samples per month; not sampled in April). Lines with different letters indicate temporal periods with significantly different fish densities (2-way ANOVA, p<0.05).

Figure 2.25. Length-frequency distributions of silver perch (Bairdiella chrysoura) collected by this program (yellow bars) and FIM (Grid 364/Turkey Creek = red bars; Grid 360 north of Turkey Creek = green bars; Grid 368 south of Turkey Creek = blue bars).

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Red drum: This species supports one of the most valuable fisheries in the Indian River Lagoon and coastal waters throughout the southeast and Gulf coasts of the United States. Adults typically spawn around inlets and nearshore waters during the fall, with larvae ultimately settling into demersal estuarine habitats (Peters et al. 1987; Rooker et al. 1997). Although they may utilize a wide array of estuarine nursery habitats, Rooker et al. 1998 determined that seagrass meadows provide better protection from predators than featureless habitats.

Red drum were observed in large numbers only in December 2015 (Figure 2.26). These newly recruited juveniles were found entirely within the Turkey Creek habitats in both the western sandy habitats and the northern region that contained more oyster shell and other structure. They were not taken in the sandy habitat outside of the mouth of Turkey Creek.

Figure 2.26. Mean (+/- S.D.) density (number/100 m2) of red drum (Sciaenops ocellatus) captured monthly from inside Turkey Creek (typically 8 samples per month) and just north of the mouth of Turkey Creek (2 samples per month; not sampled in April).

A comparison of length-frequency data of the juvenile red drum collected inside Turkey Creek in December 2015 with data collected by the FIM Program show that the fish inside Turkey Creek were significantly smaller than juveniles collected by FIM inside, north, and south of Turkey Creek (Figure 2.27; K-S test, p<0.05). Small juveniles in this size range in Tampa Bay fed on small crustaceans such as mysids, amphipods and newly-settled shrimp (Peters and McMichael, 1987). An analysis of the stomach contents of the fish collected in December 2015 is underway, and will enable determination of whether their prey are

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We anticipate that the removal of muck from Turkey Creek will increase the prey base of juvenile red drum, but the lack of seagrass or other extensive structure may reduce the survival of red drum that inhabit sandy substrate. Development of seagrasses may occur naturally in the Turkey Creek habitats, and we will conduct pilot experiments after the conclusion of dredging. Alternatively, it may also be possible to restore oyster beds or provide other habitat structure that can enhance the survival of these valuable juveniles.

40 Turkey Creek 30 Turkey Creek FWC North 20

Abundance South 10

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 More Standard Length (mm)

Figure 2.27. Length-frequency distributions of red drum (Sciaenops ocellatus) collected by this program (yellow bars) and FIM (Grid 364/Turkey Creek = red bars; Grid 360 north of Turkey Creek = green bars; Grid 368 south of Turkey Creek = blue bars).

Sea trout: Juvenile sea trout (Cynoscion spp.) were found sporadically at low densities inside Turkey Creek, but one episode of high density was detected outside the mouth of Turkey Creek in November 2015 (Figure 2.28). Primarily identifiable as spotted sea trout (Cynoscion nebulosus), these juveniles were presumably produced by adults spawning in estuarine channels during the preceding summer (Johnson and Seaman, 1986; McMichael and Peters, 1989). No significant differences were noted among sizes of juvenile seatrout collected by this sampling program and FIM sampling in adjacent habitats (Figure 2.29).

Juvenile sea trout are generally considered to prefer living in and around seagrass beds. The seagrass provides protection from predators and ready access to the planktonic prey

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(copepods) of small juvenile sea trout and epibenthic crustaceans (e.g. mysids and amphipods) of larger juveniles (McMichael and Peters, 1989).

If seagrass (Halodule wrightii) is able to grow within the dredged Turkey Creek, the removal of muck from the habitat may provide new habitat for juvenile sea trout and contribute to the fish populations within the wider IRL.

Figure 2.28. Mean (+/- S.D.) density (number/100 m2) of juvenile seatrout (Cynoscion spp.) captured monthly from inside Turkey Creek (typically 8 samples per month) and just north of the mouth of Turkey Creek (2 samples per month; not sampled in April).

15 Turkey Creek Turkey Creek FWC North 10 South

5 Abundance 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 More Standard Length (mm) Figure 2.29. Length-frequency distributions of juvenile seatrout (Cynoscion spp.) collected by this program (yellow bars) and FIM (Grid 364/Turkey Creek = red bars; Grid 360 north of Turkey Creek = green bars; Grid 368 south of Turkey Creek = blue bars).

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Sheepshead: This species is the target of many anglers fishing from docks or by the US 1 bridge in Turkey Creek. Adults use their strong jaws and teeth to feed on barnacles and other hard-shelled organisms attached to the hard substrates, and they are thus readily accessible to anglers fishing from docks. Jennings (1985) reports that sheepshead apparently spawn in nearshore waters in spring, with larvae recruiting to estuarine habitats. Upon settlement, they initially feed on soft-bodied demersal prey in seagrass and sandy sediments, switching to hard-shelled prey as they grow.

As expected from the seasonal spawning pattern, juvenile sheepshead were found in late spring through mid-summer, but primarily near the hard sand substrates outside Turkey Creek (Figure 2.30). A comparison of length data from this survey and the FIM surveys suggest that recruitment into the region comes from the south (Figure 2.31). The largest fish taken in our survey were obtained when we were able to seine around the periphery of a bed of oyster shells, and near dock structures.

Figure 2.30. Mean (+/- S.D.) density (number/100 m2) of sheepshead (Archosargus probatocephalus) captured monthly from inside Turkey Creek (typically 8 samples per month) and just north of the mouth of Turkey Creek (2 samples per month; not sampled in April).

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Figure 2.31. Length-frequency distributions of sheepshead (Archosargus probatocephalus) collected by this program (yellow bars) and FIM (Grid 364/Turkey Creek = red bars; Grid 360 north of Turkey Creek = green bars; Grid 368 south of Turkey Creek = blue bars).

Fish Community Similarity: The overall similarity in fish community composition among sites was assessed to determine if Turkey Creek supports an assemblage of fishes that differs from the surrounding habitats. Three analyses of similarity (ANOSIM) were conducted, using a Bray-Curtis similarity index. Interpretation of the ANOSIM focuses on the R-values that indicate similarity of paired populations or data sets. R-values are restricted to the range 0 to 1. R = 0 indicates complete overlap (no difference in species composition between sites) while R = 1 indicates complete separation (none of the species found in site 1 are present in site 2 and vice versa).

First, two data sets collected within Turkey Creek were compared to test if the two data sets provided an internally consistent assessment of community structure. The data sets include our seine data collected in 2015 and FIM data collected with a similar seine net inside Turkey Creek from 1990 to 2014. The ANOSIM R-value for the comparison of our data and the FIM data is 0.296 (p = 0.001), indicating that there is a similarity between the data sets (Figure 2.32). The inherent variation in FIM population estimates obtained over a 25-year period, reflecting annual variation in fish population dynamics and environmental conditions, and our more intense sampling within 9 months of a single year contribute to the R-value of 0.296.

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Figure 2.32. Analysis of Similarity (ANOSIM) results of a comparison of data collected from within Turkey Creek; our study (FIT) which collected data for 9 months in 2015, and the FIM data set which collected data from 1990 to 2014.

Comparisons of our fish data collected inside Turkey Creek to that collected by FIM from sites along the exposed western shore of the Indian River Lagoon (up to 1 km north and 1 km south of the mouth of Turkey Creek), show lesser similarities in community structure among habitats that found within Turkey Creek. The community assessment of fishes north of Turkey Creek and within Turkey Creek generated an ANOSIM R-value = 0.406 (p = 0.001) (Figure 2.33). A similar comparison of fish communities south of Turkey Creek and within Turkey Creek (Figure 2.34) detected a stronger difference in community structure (ANOSIM R-value = 0.471 (p = 0.01).

As we complete a full year of sampling in March, we will repeat these community assessments, using a two-way ANOSIM that will enable assessment of seasonality as well as spatial patterns in community structure. The results of these analyses may be of significant use in characterizing the structure of the fish community within Turkey Creek before and after muck removal.

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Figure 2.33. Analysis of Similarity (ANOSIM) results of a comparison of our data collected from within Turkey Creek in 2015 and the FIM data set from Grid 360 north of the mouth of Turkey Creek from 1990 to 2014.

Figure 2.34. Analysis of Similarity (ANOSIM) results of a comparison of our data collected from within Turkey Creek in 2015 and the FIM data set from Grid 368 south of the mouth of Turkey Creek from 1990 to 2014.

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2.5 Conclusions

Seagrasses and Drift Algae

The area to be dredged (Turkey Creek) has scattered seagrass (Halodule wrightii), but they are sparse and no patches were captured in transect quadrats. The intermediate organic sediments of Turkey Creek likely contribute, and may be the primary reason, for seagrasses struggling in what would otherwise appear to be an ideal location. In addition to the accumulation of organic sediments stressing the seagrasses, the drift algae, which likely benefit from the abundance of nutrients fluxing into the water column from benthic and suspended sediments, also shade, smother and stress struggling H. wrightii. It is anticipated that dredging of FGORS sediments in this location could potentially improve water column and benthic conditions for seagrasses in Turkey Creek.

This collection of 2015 baseline data, encompassing regular seasonal distributions and variations in the absence of any dredging, will allow for comparisons of seagrass growth during and after future dredging. In addition, the simultaneous monitoring of seagrasses in the IRL locations will allow future comparisons with areas less influenced or uninfluenced by dredging activity. Seagrasses, being an indicator of environmental health, a food source for large animals, and a nursery ground for many fisheries, will help in the assessment of the success of future environmental muck dredging. Drift algae, while food and habitat themselves, are also competitive with seagrasses and more effective at using excess nutrients. Drift algae are thus also important as a form of reciprocal indication of water quality relative to seagrasses. Seagrass and drift algae baseline data are critical to future evaluations of potential environmental improvements.

Benthic Infauna

Benthic invertebrate animals are intimately connected with the sediments in which they live and are likely to be most affected by, and responsive to, changes in those sediments. This study has shown species richness, diversity, and the abundances to vary with some predictability with the degree of FGORS characteristics in sediments. Highly organic sediments have fewer numbers of individuals and lower diversity and richness. FGORS qualifying fully as “muck” usually have no animal life. Rare occasions where animals were observed in muck were not bolstered by consistency in replicate samples, and it seems likely that these few animals were interlopers, possibly even stressed or dying in the inhospitable environment. The correlations of infaunal communities with FGORS characteristics give rise to the hope they may serve as effective indicators of change in sediment and water quality. As dredging occurs in Turkey Creek, the exposed sediments will be subsequently colonized by infaunal organisms. Sandier benthic sediments with fewer organics, a desirable outcome

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Fishes

Turkey Creek currently supports an abundant and diverse assemblage of fishes. The composition of the fish assemblage changes rapidly as pelagic schooling species, such as the numerically dominant anchovies, mullets and herrings, move into and out of the region. Larger predatory fishes such as jacks, tarpon and red drum are assumed to track the movements of the abundant prey species.

The species composition and abundance of demersal juvenile fishes changes more slowly, reflecting seasonal patterns in reproduction and growth that vary among species. The most abundant demersal juveniles are mojarras, some species of which appear to persist in the region throughout much of the year. The most important fishery species that utilize the demersal Turkey Creek habitat include juvenile red drum in winter and sheepshead in the late spring and summer. These juveniles feed on benthic infauna and epifauna, which are very sparse in muck habitats.

The removal of muck may increase the area where a benthic prey community can develop, and a larger habitat area where juveniles can forage on the prey. The complexity of the substrate presently exposed in Turkey Creek, and to be exposed after muck removal, may further influence the ability of juvenile fishes to avoid predators.

We will attempt, working with Sea and Shorelines, LLC, we will attempt to determine if seagrasses can indeed thrive within the outer Turkey Creek basin after the completion of dredging. Another form of habitat complexity that can enhance juvenile fish survival is the physical complexity provided by living or dead oyster shell bars, rocks and other hard substrate. These complex habitats can be developed below the photic zone of the turbid habitat, or even in shallow water if seagrasses do not thrive in the ecosystem.

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2.6 References

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Alves E, Martins MV, Zaaboub N, Frontalini F, Pereira E, Miranda P, Mane M, Rocha F, Laut L, El Bour M. 2015. Environmental quality assessment of Bizerte Lagoon (Tunisia) using Foraminifera assemblages and a multiproxy approach. PLoS ONE 10(9): e0137250. doi:10.1371/journal.pone.0137250.

Boltovskoy E, Scott DB, Medioli FS. 1991. Morphological variations of benthic foraminiferal tests in response to changes in ecological parameters: a review. Journal of Paleontology 65:175-185.

Buzas, M.A., L.C. Hyak, J.A. Jett, S.A. Reed 2015. Pulsating Patches: History and Analysis of Spatial, Seasonal, and Yearly Distribution of Living Benthic Foraminifera. Smithsonian Contributions to Paleobiology. 97:1-91.

Colburn DF, Baskin JA. 1998. A morphological study of Ammonia parkinsoniana from Laguna Madre and Baffin Bay, Texas. Gulf Coast Association of Geological Societies Transaction, 40:11-19 Cooksey C, Hyland J. 2007. Sediment quality of the Lower St. Johns River, Florida: An integrative assessment of benthic fauna and general characteristics. Marine Pollution Bulletin 54:9–21

Cushman JA. 1980. Foraminifera: Their Classification and Economic Use. Cambridge: Harvard UP. Print. Florida Fish and Wildlife Conservation Commission. 2003. Florida Seagrass Managers Toolkit. St. Petersburg, FL.

Florida Fish and Wildlife Conservation Commission. 2014. Fisheries Independent Monitoring Program, Detailed Gear Descriptions, App.10.1. St. Petersburg, FL.

Fonseca MS, Kenworthy WJ, Thayer GW. 1998. Guidelines for the conservation and restoration of seagrasses in the United States and adjacent waters. NOAA, Decision Analysis Series No. 12. Silver Spring, MD

Frontalini F, Curzi D, Giodano FM, Bernhard JM, Falcieri E, Corccioni R. 2015. Effects of lead pollution on Ammonia parkinsoniana (foraminifera): ultrastructural and microanalytical approaches. European Journal of Histochemistry 59(1). DOI: 10.4081/ejh.2015.2460.

Gonzalez-Ortiz V; Alcazar P; Vergara JJ, Perez-Llorens JL, Brun FG. 2014. Effects of two antagonistic ecosystem engineers on infaunal diversity. Estuarine, Coastal and Shelf Science 139:20-26.

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Hallock P, Lidz BH, Cockey-Burkhard EM, Donnelly KB. 2003. Foraminifera as bioindicators in coral reef assessment and monitoring: the FORAM Index. Foraminifera in Reef Assessment and Monitoring. Environmental Monitoring and Assessment 81:221-238.

Hanke MR, Smith KJ, DiGirolamo AL. 2013. Spatial approach to understanding habitat utilization by silver perch (Bairdiella chrysoura) in northeast Florida estuaries. Florida Scientist 76:467-477.

Hoese HD, Moore RH. 2008. Fishes of the Gulf of Mexico: Texas, Louisiana, and Adjacent Waters. 2nd ed. Texas A&M University Press.

Holzmann M. 2000. Species concept in Foraminifera: Ammonia as a case study. Micropaleontology 46: 21–37.

Hori M, Suzuki T, Monthum Y, Srisombat T, Tanaka Y, Nakaoka M, Mukai H. 2009. High seagrass diversity and canopy-height increase associated fish diversity and abundance. Marine Biology 156:1447-1458.

Ishman SE, Graham I, D’Ambrosio J. 1997. Modern benthic foraminiferal distributions in Biscayne Bay: analogs for historical reconstructions. USGS Open-File Report 97-34.

Jennings CA. 1985. Species profiles: Life histories and environmental requirements of coastal fishes and invertebrates (Gulf of Mexico): Sheepshead (Archosargus probatocephalus). U.S. Fish and Wildlife Service, Biological Report 82-11.29.

Johnson DW, Seaman W Jr. 1986. Species profiles: Life histories and environmental requirements of coastal fishes and invertebrates (South Florida): Spotted seatrout (Cynoscion nebulosus). U.S. Fish and Wildlife Service, Biological Report 82-11.43.

Jorissen FJ. 1988. Benthic Foraminifera from the Adriatic Sea; principles of phenotypic variation. Utrecht Micropaleontological Bulletins 37:7-139.

Karlsen AW, Cronin TM, Ishman SE, Willard DA, Kerhin R, Holmes CW, Marot M. 2000. Historical trends in Chesapeake Bay dissolved oxygen based on benthic Foraminifera from sediment cores. Estuaries 23: 488–508. Kerschner BA, Peterson MS, Gilmore RG Jr. 1985. Ecotopic and ontogenenetic trophic variation in mojarras. Estuaries 8:311-322.

Lippson AJ, Moran RL. 1974. Manual for identification of early developmental stages of fishes of the Potomac River estuary. Environmental Technology Center, Martin Marietta Corp.

Mason WT Jr. 1998. Macrobenthic Monitoring in the Lower St. Johns River, Florida. Environmental Monitoring and Assessment 50(2):101-130. 2-48

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McMichael RH Jr., Peters KM. 1989. Early life history of spotted seatrout, Cynoscion nebulosus (Pisces: Sciaenidae), in Tampa Bay. Estuaries 12:98-110.

Morris LJ, Hall LM, Virnstein RW. 2001. Field guide for fixed seagrass transect monitoring in the Indian River Lagoon. St. Johns River Water Management District, Palatka, Florida

Mota PJ, Clifton, KB, Hernandez P, Eggold B, Giordano SD, Wilcoy R. 1995. Feeding relationships among nine species of seagrass fishes of Tampa Bay, FL. Bulletin of Marine Science 56:185-200.

Paperno RM, Tremain DM, Adams DH, Sebastian AP, Sauer JT, Dutka-Gianelli J. 2006. The disruption and recovery of fish communities in the Indian River Lagoon, Florida, following two hurricanes in 2004. Estuaries and Coasts 29:1004–1010.

Paperno RM, Mille KJ, Kadison, E. 2001. Patterns in species composition of fish and selected invertebrate assemblages in estuarine subregions near Ponce de Leon Inlet, Florida. Estuarine, Coastal and Shelf Science 52:117-130.

Peters KM and McMichael RH. 1987. Early life history of the red drum, Sciaenops ocellatus (Pisces: Sciaenidae), in Tampa Bay, Florida. Estuaries 10:92-107.

Phlips, EJ, Badylak S, Grosskopf T. 2002. Factors a ecting the abundance of phytoplankton in a restricted subtropical lagoon, the Indian River Lagoon, Florida, USA. Estuarine, Coastal and Shelf Science 55:385–402. ﬀ

Ray C, Robins CR. 1999. A Field Guide to Atlantic Coast Fishes. Houghton Mifflin Harcourt Press.

Rooker JR, Holt GJ, Holt, SA. 1997. Condition of larval and juvenile red drum (Sciaenops ocellatus) from estuarine nursery habitats. Marine Biology 12:387-396.

Rooker JR, Holt GJ, Holt, SA. 1998. Vulnerability of newly settled red drum (Sciaenops ocellatus) to predatory fishes: is early-life survival enhanced by seagrass meadows? Marine Biology 131:145-151.

Rooker JR, Holt SA, Soto MA, Holt GJ. 1998. Post settlement patterns of habitat use by sciaenid fishes in subtropical seagrass meadows. Estuaries 21:318-327.

Sedberry GR. 1987. Feeding habits of sheepshead, Archosargus probatocephalus, in inshore reef habitats of the southeastern continental shelf. Northeast Gulf Science 9:29-39.

Sen Gupta B, Turner RE, Rabalus HH. 1996. Seasonal oxygen depletion in continental-shelf waters of Louisiana: Historical record of benthic foraminifers. Geology 24:227- 230.

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Schönfeld J, Alve E, Geslin E, Jorissen F, Korsum S, Spezzaferri S. 2012. The FOBIMO (FOraminiferal BIo-MOnitoring) initiative—Towards a standardized protocol for soft-bottom benthic foraminiferal monitoring studies. Marine Micropaleontology 94-95:1-13.

Thomas E, Gapotchenko T, Varekamp JC, Mecray EL, Buchholtz ten Brink MR. 2000. Benthic Foraminifera and environmental changes in Long Island Sound. Journal of Coastal Research 16:641-655.

Trefry J, Trocine R. 2011. Metals in sediments and clams from the Indian River Lagoon, Florida: 2006–7 versus 1992. Florida Scientist 74:43-62.

Tremain DM, Adams DH. 1995. Seasonal variations in species diversity, abundance, and composition of fish communities in the northern Indian River Lagoon, Florida. Bulletin of Marine Science 75:171-192.

Tunberg, BG, S Jones, SA Reed, Stephens, MC. 2008a. Pre and post dredge benthic environmental monitoring in Sebastian River. First Phase Final Report to St. Johns River Water Management District (November 2008). 44 pp. (Smithsonian Institution Project No. 786081)

Tunberg BG; Jones; Reed, SA; Stephens, M C. 2008b. Ecological disturbances in the St. Lucie estuary and the southern Indian River Lagoon, eastern Florida, elucidated through macrobenthic monitoring. Ocean Sciences Meeting: From the Watershed to the Global Ocean, Orlando, FL. United States Geological Survey. 2016. USGS 02250030 Turkey Creek at Palm Bay, FL. http://waterdata.usgs.gov/usa/nwis/uv?site_no=02250030.

Virnstein RW, Morris LJ. 1996. Seagrass preservation and restoration: A diagnostic plan for the Indian River Lagoon. St. Johns River Water Management District, Tech. Memorandum No. 14, Palatka, Florida.

Waggy GL, Peterson MS, Comyns BH. 2007. Feeding habits and mouth morphology of young silver perch (Bairdiella chrysoura) from the north central Gulf of Mexico. Southeastern Naturalist 6:743-751.

Willard DA and Cronin TM. 2007. Paleoecology and ecosystem restoration: case studies from Chesapeake Bay and the Florida Everglades. Frontiers in Ecology and the Environment 5:491–498.

Wong MC, Dowd M. 2015. Patterns in taxonomic and functional diversity of macrobenthic invertebrates across seagrass habitats: A case study in Atlantic Canada. Estuaries and Coasts 38:2323-2336.

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1. 2. Chapter 3 The Efficiency of Muck Removal from the Indian River Lagoon and Water Quality after Muck Removal

John H. Trefry, Robert P. Trocine, Austin L. Fox, Stacey L. Fox, Jessica E. Voelker, Katherine M. Beckett Florida Institute of Technology, Melbourne, Florida 32901

3.1 Summary

Muck removal is an integral part of the restoration process in the Indian River Lagoon (IRL) system. This fine-grained, organic-rich material (muck) (1) is easily resuspended to increase turbidity, (2) consumes oxygen, (3) creates an inhospitable benthic habitat, (4) serves as a reservoir for potential pollutants and (5) is an internal source of dissolved nitrogen and phosphorus that diffuse into lagoon waters at a rate commensurate with external sources in the North IRL. This study began in February 2015 with a muck survey of Turkey Creek in advance of proposed dredging during 2016. Little or no muck was present in the adjacent IRL near the mouth of Turkey Creek in contrast with layers that were 1- to 3-m thick throughout most of the lower creek. The estimated total volume of wet muck in the creek from this study is 111,000 m3 (145,000 yd3). Muck sediments from the creek contained >75% water by weight (>90% water by volume), 76- 99% silt + clay, and 11-22% organic matter (4-7% organic carbon, 0.4-0.8% organic N and 0.10- 0.17% total phosphorus). These values match earlier characterizations of muck deposits.

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railroad bridge (4-6 µM; 0.06-0.08 mg N/L) relative to average values near the mouth of Turkey Creek of ~1 µM (0.014 mg N/L).

3.2 Introduction

Muck removal from the Indian River Lagoon (IRL) and adjacent creeks is an important component of the overall lagoon restoration. Improved water quality is a primary goal of muck dredging because as water quality improves, the chance for successful restoration of the ecosystem is greatly enhanced. We believe that muck removal must be relatively complete because residual muck still releases nutrients and impedes the recovery of seagrass and bottom-dwelling organisms. This assumption certainly can be tested during this study that was designed to address both muck removal and water quality issues in Turkey Creek, one of the sites to be dredged in 2016 with recent funding from the State of Florida.

The goal of this study was to obtain a detailed data set that describes the distribution and composition of muck and water quality parameters in Turkey Creek so that an assessment of the effectiveness of dredging can be carried out. To meet this goal, the following activities were completed in Turkey Creek during 2015: (1) determination of the spatial distribution, total volume

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of Technology Final Report, July 2016 and composition of muck sediments, (2) nine monthly water quality surveys at five locations in the study area with analysis of dissolved and particulate chemicals and (3) as a complementary effort to this study, some sediment flux measurements were made to determine releases of nitrogen and phosphorus from bottom sediment to the overlying water column.

Black, organic-rich (>10% organic matter), mud-rich (>60% silt + clay), high water content (>75% water by weight, >90% water by volume) sediments (referred to loosely as muck in this report) are not naturally occurring in the IRL. Earlier studies of muck in the IRL (Trefry et al., 1987, 1990) reported muck, as defined above, to be most prevalent in creeks adjacent to the lagoon (e.g., Crane Creek, Turkey Creek), the Intracoastal Waterway and deeper pockets of water near tributary sources. A 1989 muck survey of the Indian River Lagoon System from Ponce de Leon Inlet to St. Lucie Inlet concluded that the spatial occurrence of muck was limited to <10% of the lagoon (Trefry et al., 1990). These fine-grained, organic-rich sediments are a primary repository for contaminants in coastal estuaries (National Research Council, 1997), including the IRL (Trocine and Trefry, 1996, Trefry and Trocine, 2011). Identifying the distribution of anoxic muck sediments and definitively identifying changes in environmental quality after dredging may provide important insight regarding the health of the lagoon and future remediation strategies.

In 2006-7, Trefry and Trocine (2011) revisited 73 locations in the IRL to re-assess muck deposits that were sampled in 1989. Muck layers increased in thickness at 51 of 73 stations over 17 years, yet 7 of 11 stations that contained no muck in 1989 remained muck free. The total muck thickness for 2006–7 (~63 cm/site) was ~67% greater than in 1989 (~38 cm/site). They estimated that muck covered ~10% of the lagoon during both periods. Clearly, the muck problem had not gone away.

Concentrations of metals and organic contaminants in muck sediments were determined previously and a sizeable data set is available (Windsor and Surma, 1993; Trocine and Trefry 1996; Windsor, 2004; Trefry et al., 2011). Results for potential contaminants were assessed using sediment quality guidelines wherein an Effects Range-Low (ERL) and Effects Range-Median (ERM) are used to identify concentrations that may induce sediment toxicity (Long et al., 1995). The ERL and ERM are defined as the 10th and 50th percentiles, respectively, from a list of ascending concentrations of contaminants in sediments that may cause adverse biological effects. These sediment quality guidelines were developed to identify specific sites where additional investigation is warranted rather than specifically identifying toxic sediment. For metals, no concentrations of the five metals with realistic values for the ERL and ERM (Ag, Cd, Hg, Pb or Zn) exceeded their respective values for the ERM in surface sediments from the IRL in 1992 or 2006–7 (Trefry and Trocine, 2011). Surface sediments from Crane Creek and Eau Gallie Harbor had Hg and Zn concentrations that exceeded the ERL during both 1992 and 2006-7 (Trefry and Trocine, 2011). Lead concentrations exceeded the ERL at 4 locations in 2006–7 relative to none in 1992, possibly due to inputs from old upstream sources during the 2004 hurricanes. Nearly all muck sediment samples collected in

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2006-7 had lower concentrations of total polycyclic aromatic hydrocarbons (TPAH) than in 1992. No TPAH concentrations exceeded the ERM or ERL (ERL = 4 µg/g) during these sediment surveys (Windsor, 2004, Trefry et al., 2008). Overall, no serious problems with metals and organic substances have been reported for the IRL System. Instead, the primary issue of concern centers on nutrients and algal blooms.

Very few studies of the impacts of dredging in creeks have been carried out for the IRL System. About ~60,000 m3 (86,000 yd3) of sediment were removed from Crane Creek during 1998; yet, Trefry et al. (2004) estimated that ~82,000 m3 of muck were present in the creek in 2002, with more than half deposited east of U.S. Route 1. These results are largely due to the fact that removal of muck from Crane Creek was limited because no dredging occurred near docks and seawalls. Based on measured sedimentation rates, the annual volume of sediment deposited in Crane Creek was estimated to be 800 ± 300 m3/yr. At that rate, an amount of sediment equivalent to the 60,000 m3 dredged in 1998 would be deposited in ~75 years (Trefry et al., 2004). As a consequence of dredging, Garcia (1998) showed that the salt wedge in Crane Creek moved several hundred meters upstream and generally increased dissolved oxygen concentrations, except in deeper depressions (up to 4.2 m) created by dredging. This same scenario is predicted for Turkey Creek. Previously in Turkey Creek, Trefry et al. (2002) found that only a thin veneer of fine-grained sediment remained after dredging muck from the Palm Bay area between U.S. Route 1 and the mouth of the creek. This area has had ≥1 m of muck added since 2002.

3.3 Approach

3.3.1 Muck Survey, Sediment and Water Collection

This study was initiated with a muck survey that was carried out during February 2015 using a 4- cm diameter, capped polyvinyl chloride (PVC) pole with a T-shaped handle; the pole was marked in centimeter gradations (Figure 3.1A). The pole was lowered into the water column until the surface layer of sediment was encountered; this depth was recorded as the water depth. The pole was then pushed into the sediment until a firm bottom was struck and the total depth minus the water depth was recorded as the thickness of the muck layer. Muck often adhered to the pole along the entire muck interval to provide validation of the thickness of the muck layer. The survey included 253 probe measurements of water depth and muck thickness within a gridded area of the creek (grid and data in Appendix A). The data for water depth and muck thickness were tabulated and contour maps were generated using ArcGIS (Version 10.2.2.3552, Esri, Redlands, CA).

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(A) (B)

TC1

TC3 TC2

TC4

TC5

(C)

Figure 3.1. (A) Using a PVC pole to determine water depth and muck thickness, (B) map showing sampling locations for sediment (labelled A-I) and water (labelled TC1-TC5), larger scale maps are presented in Section 3.4.1, (C) pumping water for chemical analysis using a peristaltic pump with Tygon tubing, and (D) SEAL AA3 three-channel auto-analyzer for nutrient analysis.

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Sediment samples for chemical analysis were collected at nine locations (Figure 3.1B) using a small ponar grab. Sediment from the top 2 cm of the grab was placed in double Ziploc bags for grain size and in polycarbonate vials (~70 mL) for other chemical analyses.

Nine pre-dredging water quality surveys were carried out during 2015 (April-December). Water samples were collected from 2-5 depths at the same five stations during each survey (Figure 3.1B). Vertical profiles for salinity, temperature, pH and dissolved oxygen were obtained using a YSI 6600 V2 sonde (Yellow Springs Instruments). The sonde was calibrated at the beginning of each day following the manufacturer’s specifications. Discrete samples were collected through Tygon tubing attached to a peristaltic pump (Figure 3.1C). Samples were placed in acid-washed low- density polyethylene bottles and stored in coolers until returned to the Marine & Environmental Chemistry Laboratories at Florida Institute of Technology (FIT). Filtration was carried out within 2-3 hours through 47-mm diameter, 0.4-µm pore size polycarbonate filters (for Fe, Al, Si, P) and 47-mm diameter, 0.7-µm pore size glass fiber filters (for dissolved C, N and P species and particulate C and N).

3.3.2 Laboratory Analyses: Sediments

All sediment samples, except sub-samples for grain size, were freeze dried and powdered using a SPEX Model 8000 Mixer/Mill. In preparation for analysis for Al, Fe, Si and P, 10-20 mg of freeze- dried, homogenized sediment or Certified Reference Material (CRM) sediment MESS-3, from the National Research Council of Canada (NRC), were totally digested in sealed Teflon tubes using concentrated, high-purity HF and HNO3 following methods of Trefry and Trocine (1991). Complete digestion of the sediment was chosen because it accounts for the entire amount of each element in the sample.

Concentrations of Al, Fe and Si in digested sediments were determined by flame atomic absorption spectrometry (FAAS) using a Perkin-Elmer Model 4000 atomic absorption spectrometer following U.S. EPA (1991) methods. Values for P were determined by inductively coupled plasma-mass spectrometry (ICP-MS) based on EPA Method 6020 (U.S. EPA, 1991) using a Varian Model 820- MS instrument with Collision Reaction Interface and a Model SPS3 sample preparation system. Concentrations of these elements in the sediment CRM MESS-3 were within the 95% confidence intervals for certified values. Analytical precision for individual elements in sediments ranged from 0.7 to 6% (as relative standard deviation, RSD). Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

Grain size analyses were carried out using the classic method of Folk (1974) that includes a combination of wet sieving and pipette techniques. Loss on Ignition (LOI) at 550˚C was determined following the method of Heiri et al. (2001). Values for LOI estimate the fraction of

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organic matter in the sample and are used in conjunction with concentrations of organic C, total N and total P to make inferences about sediment sources. Concentrations of CaCO3 were determined by heating the sediment that had been treated for LOI at 550˚C to 950˚C following the method of Heiri et al. (2001).

Concentrations of total organic carbon (TOC) were determined using freeze-dried sediment that was treated with 10% (v/v) hydrochloric acid to remove any inorganic carbon, washed with carbon-free, high purity water (HPLC grade) and dried. Then, approximately 200-800 mg of pre- treated sediment were weighed into ceramic boats and combusted with pure oxygen at 950˚C using a LECO Corporation (St. Joseph, MI) TruMac C/N/S system with quantification of the resultant CO2 gas using an infrared detection cell. Sediment total nitrogen concentrations were determined using separate samples that were untreated prior to analysis to avoid losses of nitrogen during acidification. Nitrogen analyses of sediments also were carried out using the LECO system at 950˚C with quantification of the N2 gas produced via a thermal conductivity detector. Concentrations of C and N in the sediment CRM MESS-3, SRM #2704 and LECO reference sample 502-309 were within the 95% confidence intervals for certified values. Analytical precision was 1.5% for TOC and 2% for total nitrogen. Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

3.3.3 Laboratory Analyses: Water Dissolved Chemicals

Samples for nutrient analysis were vacuum filtered through polycarbonate filters (Poretics, 47-mm diameter, 0.4-µm pore size) in a laminar-flow hood. Ammonium was quantified following standard methods (#4500-NH3, Clesceri et al., 1989). Ammonium reacts with phenol to form indophenol with a blue color that adsorbs light at 630 nm in direct proportion to ammonium concentrations. Standards were prepared from dried ammonium chloride (Clesceri et al., 1989) and analyzed twice using UV-visible spectrometry with each batch of samples to ensure accuracy. All values were within the 95% confidence interval for the prepared standard. Analytical precision for lab duplicates (RSD) was 2.4%. Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

Concentrations of nitrate-nitrite were determined following standard methods (Jones, 1984). Nitrate is reduced to nitrite by shaking with spongy cadmium. Nitrite then reacts with sulfanilamide to form a diazo compound and is then coupled with N-(1-naphthyl) ethylenediamine dihydrochloride to form a pink azo dye. The absorbance of this azo dye was determined by UV- visible spectrometry at 540 nm. The National Institute of Standards and Technology (NIST) traceable Dionex 5-Anion Standard was analyzed as a reference standard with each batch of samples to ensure accuracy; all values were within 10% of the known concentration. Analytical

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precision for lab duplicates (RSD) was 6.1 ± 4.8%. Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

Concentrations of total dissolved nitrogen were determined using a SEAL AA3 HR Continuous Segmented Flow AutoAnalyzer following manufacturer’s method no. G-218-98. Organic and inorganic nitrogen compounds were converted to nitrate using UV and persulfate digestion. Nitrate was reduced to nitrite using a cadmium column. Nitrite was reacted with sulfanilamide to form a diazo compound which was coupled with N-(1-naphthyl) ethylenediamine dihydrochloride to form a pink azo dye. The absorbance of this azo dye was determined by UV-visible spectrometry at 540 nm. Standards were prepared from dried ammonium chloride (Clesceri et al., 1989) analyzed twice with each batch of samples to ensure accuracy; all values were within 10% of the known concentration. Analytical precision for lab duplicates (RSD) was 2.1 ± 1.8%. Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

Concentrations of ortho-phosphate were determined following method 4500-P (Clesceri et al., 1989). Ortho-phosphate was reacted with ascorbic acid, molybdate and antimony to yield a phospho-molybdenum blue complex. The absorbance at 880 nm was determined using UV-visible spectrometry. The NIST-traceable Dionex 5-Anion Standard was analyzed as a reference standard with each batch of samples to ensure accuracy; all values were within 95% confidence interval for this standard. Analytical precision for lab duplicates (RSD) averaged 1%.

Alkalinity was determined following method 2320-B (Clesceri et al., 1989). Samples were titrated with 0.01N HCl to a known endpoint. Alkalinity in mg CaCO3/L is directly proportional to the volume of acid added. Standard seawater solution (OSIL, UK) was analyzed as a reference standard with each batch of samples; all values were within 95% confidence interval for the standard. Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

Concentrations of total dissolved phosphorus were determined using a SEAL AA3 HR continuous Segmented Flow AutoAnalyzer following manufacturer’s method no. G-219-98. UV and persulfate digestion were used to free organically-bound phosphorus. Ortho-phosphate was reacted with ascorbic acid, molybdate and antimony to yield a phospho-molybdenum blue complex. The absorbance at 880 nm was determined using UV-visible spectrometry. The NIST-traceable Dionex 5-Anion Standard was analyzed as a reference standard with each batch of samples to ensure accuracy; all values were within 10% of the known concentration. Analytical precision for lab duplicates (RSD) was 2.6 ± 2.4%.

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3.3.4 Laboratory Analyses: Water Particulate Chemicals

Samples of suspended matter were collected by vacuum filtering water through polycarbonate filters (Poretics, 47-mm diameter, 0.4-μm pore size) in a laminar-flow hood in our clean room at FIT. Prior to the field effort, the filters were acid washed in 5N HNO3, rinsed three times with deionized water (DIW), dried and then weighed to the nearest μg under cleanroom conditions. Precision for replicate filtrations averaged <4% (i.e., ±0.04 mg/L). Samples for particulate organic carbon (POC) were filtered through pre-combusted Gelman Type A/E glass fiber filters mounted on acid-washed filtration glassware within a Class-100 laminar-flow hood. Particle-bearing filters were sealed in acid-washed petri dishes, labeled and then double-bagged in plastic and stored until dried and re-weighed at FIT.

Suspended particles, as well as separate milligram quantities of standard reference material (SRM) #2704, a river sediment issued by the NIST, were digested in stoppered, 15-mL Teflon test tubes using Ultrex II HNO3 and HF as described by Trefry and Trocine (1991). Concentrations of particulate Al, Fe and Si were determined by flame atomic absorption spectrometry and concentrations of particulate P were determined by inductively-coupled plasma mass spectrometry (ICP-MS) using a Varian 820 instrument. Analytical precision for individual elements in sediments ranged from 1-5%. Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

Concentrations of particulate organic carbon (POC) and total nitrogen were determined by first treating particles on the glass fiber filter with 10% (v/v) hydrochloric acid to remove any inorganic carbon, washed with carbon-free, high purity water (HPLC grade) and dried. Then, the filters with approximately 200-800 mg of pre-treated suspended sediment were weighed into ceramic boats and combusted with pure oxygen at 950˚C using a LECO TruMac C/N/S system with quantification of the resultant CO2 gas using an infrared detection cell. Total nitrogen concentrations were determined using separate glass fiber filters that were untreated prior to analysis to avoid losses of nitrogen during acidification. Nitrogen analyses of suspended particles also were carried out using the LECO system at 950˚C with quantification of the N2 gas produced via a thermal conductivity detector. Concentrations of C and N in the sediment CRM MESS-3, SRM #2704 and LECO reference sample 502-309 were within the 95% confidence intervals for certified values. Analytical precision was 1.5% for TOC and 2% for total nitrogen. Additional QA/QC information and data are provided in Section 3.3.5 and Appendix B.

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3.3.5 Quality Assurance and Quality Control (QA/QC)

The QA/QC program used in the Marine & Environmental Chemistry Laboratories at FIT for sediment and water collection and analysis followed the general guidelines provided below.

(i) Sample Handling. Sediment samples were transferred to a refrigerator or if sampled as cores, were immediately processed for sub-sampling (and then refrigerated if necessary). Water samples were collected and preserved using appropriate containers and reagents. Solutes were measured within appropriate holding times. All water samples were kept chilled, either on ice or in refrigerators, until analyzed.

(ii) Quality Control Measurements for Analyses. Quality control measures included instrument calibration, matrix spike analysis, field replicates, duplicate sample analysis, standard reference material analysis, procedural blank analysis, and standard checks. With each batch of 20 field samples a procedural blank, standard reference materials, a field and laboratory duplicate, and a matrix spike sample were analyzed. Data quality objectives for these quality control measurements are provided in Table 3.1.

(iii) Matrix spike analysis. A matrix spike sample (method of additions analysis) was run with every batch of 20 samples. Results from the method of additions analysis provide information on the extent of any signal suppression or enhancement due to the matrix. When necessary (spike results outside 85-115% limit), samples were analyzed by methods of additions.

(iii) Duplicate sample analysis. To estimate precision of the analyses, a duplicate field sample was analyzed with each batch of 20 samples.

(iv) Standard reference material analysis. A common method used in evaluating the accuracy of environmental data is to analyze standard reference materials, samples for which consensus or "accepted" analyte concentrations exist. The marine sediment (MESS3) from the NRC of Canada and a river bottom sediment from the NIST (#2704, Buffalo River Sediment) were analyzed with every batch of sediment samples.

(vi) Procedural blank analysis. A procedural blank was processed and analyzed with each batch of samples to monitor potential contamination resulting from laboratory reagents, glassware, and processing procedures.

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Table 3.1. Data quality objectives for the proposed study.

Element or Sample Type Minimum Frequency Data Quality Criteria Objective/Acceptance Initial Calibration Prior to every batch of samples 3-5 point curve depending Standard Curve on the element and a blank Correlation coefficient r ≥ 0.999 for all analytes Continuing Calibration Must end every analytical % RSD ≤15% for all sequence or after every 8-10 analytes samples Certified and Standard Two per batch of 20 samples Values must be within 20% Reference Materials of accepted values for >85% of the certified analytes Method Blank Two per batch of 20 samples No more than 2 analytes to exceed 5x MDL Matrix Spike and Two per batch of 20 samples 80-120% Spike Method Blank Lab Duplicate Two per batch of 20 samples RSD <25% for 65% of analytes

Results for accuracy, precision, matrix spikes, field replicates and method detection limits are provided in Appendix B.

Electronic balances used for weighing samples and reagents were calibrated prior to each use with their internal electronic calibration and then verified with certified standard weights (NIST- traceable). All pipets (electronic or manual) were calibrated prior to use. Each of the spectrometers used for metal analysis was initially standardized with a three- to five-point calibration; a linear correlation coefficient of r 0.999 was required before experimental samples could be analyzed. Analysis of complete three- to six-point calibrations or single standard checks occurred after every eight samples until all analyses were complete. The RSD between complete calibration and standard checks was required to be <10% or recalibration and reanalysis of the previous samples was performed.

All weighing-related manipulation of the filters used for suspended solids quantification took place under cleanroom conditions, including controlled temperature and relative humidity. Each filter was weighed twice in random order, with a minimum of 5% of the filters being weighed in triplicate. Static effects on filter weight were controlled by the placement of two 210Po anti-static devices near the weighing-pan within the balance. The standard deviation in the weights for each filter had to be <2 µg for the value to be accepted.

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3.4 Results and Discussion

3.4.1 Muck Survey

Water depths and thicknesses of muck layers were determined at 199 locations in Turkey Creek, extending from the mouth at the IRL to the Florida East Coast (FEC) railroad bridge (Figures 3.2 and 3.3). An additional 54 measurements were made either in the adjacent IRL or as replicates in Turkey Creek. The average water depth in the creek was 1.8 ± 0.9 m with a range of 0.4-4.4 m (Figure 3.2 and Table 3.2). Water depths in the creek were <1.5 m at ~50% of the stations, 1.5-3 m at ~40% of the stations and >3 m at only ~10% of the stations (Table 3.2).

IRL

U.S. Route 1

Turkey Creek

FEC Railroad Bridge

Figure 3.2. Contour map of water depth in Turkey Creek from the adjacent Indian River Lagoon (IRL) to the Florida East Coast (FEC) railroad bridge. Dots show probing locations.

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IRL

U.S. Route 1

Turkey Creek

FEC Railroad Bridge

Figure 3.3. Contour map of muck thickness in Turkey Creek from the adjacent Indian River Lagoon (IRL) to the Florida East Coast (FEC) railroad bridge. Dots show probing locations.

Results from our muck survey showed that little or no muck was present in the adjacent IRL near the mouth of Turkey Creek (Figure 3.3). This observation, coupled with the relatively shallow IRL, suggests that muck carried to the mouth of the creek and into the IRL is readily advected away from the immediate area. Likewise, little or no muck was found in shallow water (depth, 0.4- 1 m) at the northern lobe of Palm Bay in Turkey Creek, just west of the confluence of the creek with the IRL (Figure 3.3). In contrast, muck layers as thick as 3 m were found in 2- to 4-m deep water in the southern portion of the creek (Figure 3.2 and 3.3). Muck was absent from about ~26% of the stations in Turkey Creek (Table 3.2). Muck thicknesses of ~1-3.1 m were found at ~23% of the creek stations; the remaining ~51% of the creek stations contained <1 m of muck (Figure 3.3 and Table 3.2).

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Table 3.2. Water depths (n = 199) and muck thicknesses (n = 199) for Turkey Creek.

Water Depth # of Locations Muck Thickness # of Locations (m) (m) 0.4 – 1.0 42 0 52 >1.0 - 1.5 55 >0 – 0.25 37 >1.5 - 2.0 19 >0.25 – 0.50 28 >2.0 – 2.5 26 >0.50 – 0.75 23 >2.5 – 3.0 39 >0.75 – 1.0 14 >3.0 – 3.5 12 >1.0 – 1.5 15 >3.5 – 4.4 6 >1.5 – 2.0 8 >2.0 – 2.5 9 >2.5 – 3.1 13

Muck thicknesses >1.5 m were typically (37 of 44 stations) found at water depths of 1.5-3.1 m (Figure 3.4A). Data for the 52 locations with no detectable muck plot along a straight line labelled “+0 m” on a plot of water depth versus muck + water depth (Figure 3.4B). The lines at +1 m, +2 m and +3 m (Figure 3.4B) show the increases in water depths that would be observed if all the muck was removed from each site in the creek. This increase in water depth, as much as 3 m, could increase the residence time of deeper bottom water in the creek. These new basins also may become traps for incoming fine-grained, organic-rich sediments. If so, they may become seasonally anoxic reservoirs for dissolved ammonium and hydrogen sulfide as discussed below in

(A) (B) 5 5 + 0 m + 1 m 4 4 + 2 m 3 3

2 2 + 3 m

Water Depth (m) 1

Water Depth (m) Depth Water 1

0 0 012340123456 Muck Thickness (m) Muck + Water Depth (m)

Figure 3.4. Water depth in Turkey Creek versus (A) thickness of the muck layer, and (B) muck thickness plus water depth. Lines on (B) show where no muck is found (+ 0 m) and where muck + water depth is +1, +2 and +3 m relative to water depth.

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the water quality section (3.4.3). One possible way to limit the number of traps for incoming fine- grained, organic-rich sediment is to fill them with sand (written communication, Virginia Barker). With this approach, some traps would still need to be retained to capture future inputs of muck components from upstream or undredged nearshore areas in the creek. Deeper traps would decrease the exposed surface area relative to the volume of muck.

The muck thickness data were used to estimate the total volume of wet muck in Turkey Creek from the mouth to the FEC railroad bridge. The volumes of muck in gridded areas were added to obtain a sum of 111,000 m3 (145,000 yd3) of wet muck (Appendix A shows map of gridded cells and supporting data). Contractors for Brevard County obtained a total muck volume of 176,000 m3 (230,000 yd3) using a metal rod that in many cases penetrated deeper than our PVC pipe by 15- 30 cm (6-12 inches), thereby yielding a larger muck volume. If we increase our volume of muck by adding 30 cm to our volume calculation (either to approximate the deeper penetration of the metal rod or planned dredging to ~30 cm into the underlying sand layer), we obtain a volume of 148,000 m3 (194,000 yd3). Both methods (PVC pipe and metal rod) have some limitations, yet the estimated overall agreement between the two methods is within ~20%, including a correction for the metal rod versus PVC pipe (~160,000 ± 20,000 m3 or 210,000 ± 25,000 yd3).

3.4.2 Muck Composition and Fluxes of Nitrogen and Phosphorus from Sediments

Nine representative samples of surface sediment, including both muck and sand (Figure 3.5), were collected during the muck survey and analyzed for water content, Al, Fe, Si, TOC, total N, total P, CaCO3 and grain size. Sediment % water by volume ranged from ~45% in sandy sediments (station A) to >90% in muck (stations F-H, Figure 3.5 and Table 3.3). Muck was previously defined as having >75% water (by weight or ~90% water by volume, Trefry et al., 1987, 1990). Only the four southernmost stations (F-I) contained sediment with >75% water by weight (Table 3.3). The organic matter content of sediments from the study area (expressed as LOI at 550°C) ranged from 1.6% in sandy sediment (station A) to 21.7% in muck (station F, Figure 3.5 and Table 3.3). Muck was previously defined as containing >10% organic matter (Trefry et al., 1987). Again, only the four southernmost stations (F-I) fit the original muck definition.

Three of the four samples identified as muck based on % water and LOI also met the 1987 criteria with >75% silt + clay (Table 3.4 and Figure 3.6). In contrast, sediment at station I, located in a canal south of the harbor area, contained only 35.5% silt + clay (Table 3.4 and Figure 3.6). Over time and with increased sampling, a continuum of muck compositions is evolving. We will work to refine or expand our definition of muck as this project continues.

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(A) (B) % H2O (vol) % LOI

45.9 1.6 75.7 3.5 65.5 5.3 71.3 4.7 62.8 3.4 95.7 21.7 95.2 19.8

94.4 19.9 89.1 11.1

Figure 3.5. Contour maps for muck thickness in Turkey Creek and the adjacent Indian River Lagoon (IRL). Blue dots show where surface sediments were collected. Numbers on (A) show % water in sediments by volume and (B) % loss on ignition (LOI) at 550˚C for sediments.

Table 3.3. Concentrations of selected elements in surface sediments from Turkey Creek. Station locations shown on Figure 3.5. Shading identifies samples that fit the 1987 definition of muck.

b c Al Fe Si TOC LOI CaCO3 H2O H2O N P Station (%) (%) (%) (%) (%) (%) (wt. %) (vol. %) (%) (%) A 0.29 0.25 34.7 0.20 1.6 5.2 24.6 45.9 0.03 0.01 B 2.11 1.45 31.4 1.43 5.3 4.0 54.5 75.7 0.18 0.07 C#1a 0.86 0.75 36.5 0.87 3.5 2.5 42.2 65.5 0.12 0.03 C#2a 0.82 0.73 36.3 0.89 3.4 2.5 - - 0.12 0.04 D 1.16 1.05 36.9 1.33 4.7 2.9 48.9 71.3 0.16 0.05 E 0.82 0.78 37.9 0.94 3.4 2.1 39.4 62.8 0.11 0.04 F 4.80 4.28 16.9 7.09 21.7 12.3 89.6 95.7 0.81 0.15 G 4.51 3.51 19.1 6.49 19.8 13.4 88.4 95.2 0.83 0.14 H 3.87 2.51 18.1 6.84 19.9 12.3 86.7 94.4 0.63 0.16 I 2.44 2.39 29.2 4.12 11.1 4.8 75.8 89.1 0.40 0.10 aField replicates. bTOC = Total Organic Carbon. cLOI = Loss on Ignition at 550˚C.

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Table 3.4. Grain size distribution and aluminum content for surface sediments from Turkey Creek and the adjacent Indian River Lagoon. Station locations on Figure 3.6. Shading identifies samples that fit the 1989 definition of muck.

Gravel Sand Silt Clay Silt & Clay Al Station (%) (%) (%) (%) (%) (%) A 2.6 94.7 0.5 2.2 2.7 0.29 B 0.8 82.4 8.1 8.7 16.8 2.11

C 0 91.6 3.2 5.2 8.4 0.84 D 1.6 85.3 7.2 6.0 13.2 1.16

E#1a 0 89.4 4.9 5.6 10.5 0.82 E#2a 0.1 81.8 9.0 9.0 18.0 0.82 F 0 1.3 73.5 25.2 98.7 4.80 G 0 7.3 51.4 41.3 92.7 4.51 H 0 23.8 48.0 28.1 76.1 3.87

I 0 64.9 20.4 15.1 35.5 2.44 aField replicate.

Station E Station A Sand 89.4% Sand 94.7%

Gravel 2.6% Gravel 0% Clay 2.2% Clay 5.6% Silt 0.5% Silt 4.9%

Station H Sand Station G 23.8% Silt 51.4% Silt 48.0% Sand 7.3% Gravel 0% Gravel 0% Clay 28.1% Clay 41.3%

Figure 3.6. Contour map for muck thickness in Turkey Creek and the adjacent Indian River Lagoon. Blue dots show where surface sediments were collected. Pie graphs show grain size distribution at selected stations.

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Values for LOI correlated very strongly (r >0.9) with concentrations of TOC (Figure 3.7A). The slope of the line for TOC versus LOI was 0.35; this slope means that the organic matter collected in Turkey Creek averages ~35% C. Data for both LOI and TOC were generated for this study. Concentrations of total organic carbon correlated very strongly with total P and total N (Figure 3.7B, C). The four muck samples had an average C/P molar ratio of 115, close to the Redfield ratio of 106 (published C/N/P atomic [molar] ratio of 106/16/1 in phytoplankton and in deep seawater by Redfield, 1934, Figure 3.7B). The C/P ratio for the non-muck samples was less reliable because

(A) 10 (B) 0.20 8 Muck (C/P) = 115 0.15 molar 6 Muck 0.10 4 0.05 2 TOC = 0.35 LOI - 0.28 TP = 0.019 TOC - 0.021 Sediment TOC (%) r = 0.997, n = 10, p<0.001 r = 0.98, n = 10, p<0.001 Sediment Total P (%) Sediment 0 0.00 0 5 10 15 20 25 02468 Sediment LOI at 550ºC (%) Sediment TOC (%)

(C) (D) 0.20 Muck (N/P) = 10.6 1.0 molar Muck (C/N)molar = 11.0 0.15 Muck Muck 0.10 0.5 0.05 TN = 0.107 TOC - 0.015 TP = 0.17 TOC - 0.02 r = 0.98, n = 10, p<0.001 r = 0.95, n = 10, p<0.001 Sediment Total P (%) Sediment Total N (%) 0.0 0.00 02468 0.0 0.2 0.4 0.6 0.8 1.0 Sediment TN (%) Sediment TOC (%)

Figure 3.7. (A) Sediment total organic carbon (TOC) versus sediment Loss on Ignition (LOI) at 550°C, (B) sediment total phosphorus versus sediment TOC, (C) sediment total nitrogen versus TOC and (D) sediment total phosphorus versus total nitrogen. Muck samples plot within the ovals on (B), (C) and (D). The molar ratio for the four muck samples is listed next to each oval. Solid lines and equations on each graph are from linear regression analysis, dashed lines show 95% prediction intervals, r is the correlation coefficient and p is the p statistic.

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of the very low amounts of organic matter present in the sediment. In contrast, the average molar C/N ratio of 11.0 for four muck samples (Figure 3.7C) was ~67% greater than the Redfield ratio of 6.6, suggesting that the muck sediment was depleted in N, possibly due to releases of dissolved ammonium from the muck to the water column. The average molar ratio of 10.6 for N/P was ~35% lower than 16 predicted by the Redfield ratio. This result also supports N depletion in the sediments and suggests that losses of P are relatively small and P fluxes from the sediments seem to have a lower impact on sediment P concentrations. The TOC and total N values are for organic C and organic N in sediments whereas the total P values include both organic and inorganic P where the inorganic P may be associated with weathered phosphorite rock. During 2016, we plan to analyze some samples for both organic and inorganic P and then reevaluate the C/P and N/P ratios.

Concentrations of iron in sediments from the study area also correlated strongly with Al values (Figure 3.8A); however, the slope of the line (0.78) was higher than found in typical continental crust (0.54, Wedepohl, 1995), likely the result of enhanced iron from runoff of Fe from irrigation water and/or the presence of iron- and magnesium-rich clay minerals such as vermiculite in sod from the Turkey Creek basin. Concentrations of total Si in the sediments were inversely correlated with aluminum values (Figure 3.8B). This observation is due to the presence of quartz (SiO2) sand in the sample. Indeed, the maximum concentration of Al (~5%) was found for a sample with ~17% silicon (Figure 3.8B), suggesting that the Si/Al atom ratio was ~3:1. All of this geochemical information can be used to help us identify sediment sources and look at variations and changes in sediment type following dredging.

(A) 5 (B) Turkey Creek 50 Surface Sediments Turkey Creek 4 45 Surface Sediments 40 3 35

Fe (%) 2 Si (%) 30 25 1 Fe = 0.78 (Al) - 0.07 r = 0.97, n = 10, p<0.001 20 Si = -4.9 (Al) + 40 r = 0.97; n = 10, p<0.001 0 15 0123456 012345 Al (%) Al (%) Figure 3.8. (A) Sediment total iron (Fe) versus total aluminum (Al) and (B) sediment total silicon (Si) versus Al. Solid lines and equations on each graph are from linear regression analysis, dashed lines show 95% prediction intervals, r is the correlation coefficient and p is the p statistic.

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Ongoing efforts in our Algal Blooms study (funded by St. Johns River Water Management District) seek to better address losses of N with depth (time) in sediments (e.g., Trefry et al., 2014, 2015). As a complement this project, we have collected several short (30-40 cm) sediment cores from Turkey Creek for chemical analysis to investigate changes in water content, TOC, total nitrogen and other parameters below the sediment-water interface. We continue to collect and analyze cores from Turkey Creek. Results for one core from station TC4 are presented here for perspective. Water content was >90% (by wt.) in the top 6 cm and decreased to ~83% at 32-38 cm, possibly due to upward advection of water caused by sediment compaction. The complete core contained muck as defined by >75% water by weight. Concentrations of Al were relatively uniform at 4.7 ± 0.4% and concentrations of TOC averaged 6.9 ± 0.7% with one C-rich sample (TOC = 9.24%) at 2-4 cm. Other than the C-rich layer, no discernible downcore trend was observed for TOC. Concentrations of total N were very uniform in the core with an average of 0.77 ± 0.02%; however, a decrease in the N/Al ratio was observed in the top 10 cm of the core, possibly due to diagenetic loss of N. Ongoing efforts in our Algal Blooms study seek to better address loss of N with depth (time) in sediments (e.g., Trefry et al., 2014, 2015).

H2O (% by wt) TOC (%) Total N (%) 70 80 90 100 0 5 10 15 20 0.0 0.5 1.0 1.5 2.0 0 0 0 Station TC4 Station TC4 Station TC4 10 10 10

H2O TN TN/Al 20 H2O/Al 20 20

TOC TOC/Al 30 Sediment Depth (cm) Depth Sediment Sediment Depth (cm) Depth Sediment Sediment Depth (cm) Depth Sediment 30 30

40 40 40 0 102030 01230.00.10.20.3 H O/Al 2 TOC/Al Total N/Al

Figure 3.9. Vertical profiles for (A) water content, (B) total organic carbon (TOC) and (C) total nitrogen plus ratios of the three components to aluminum (Al) for a sediment core from station TC4 (location in Figure 3.1).

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Prompted by high ammonium values in bottom water at station TC5 (see Section 3.4.3.2 below), we added another component to this study by collecting sediments from station TC5 (location on Figure 3.1B) on June 6, 2015 to determine fluxes of nitrogen and phosphorus from sediments to the overlying water column. We carried out the flux measurements as described in Trefry et al. (2014). Interstitial water was collected from duplicate sediment cores using whole-core squeezers (Trefry et al., 2014). Ammonium concentrations in the interstitial water peaked at near 1,000 µM (14 mg N/L), almost 200 times greater than in the bottom water. The calculated flux of dissolved ammonium from sediments at station TC5 (~16 nmol/cm2/hr) is equivalent to ~20 metric tons N/km2/yr. This flux is similar to previously obtained values for sediments from Eau Gallie Harbor and the IRL near Rockledge where the muck composition is similar to that found in Turkey Creek; the average N flux for the North IRL is 10 tons N/km2/yr (Trefry et al., 2014, 2015). The flux for phosphate at station TC5 was 1.5 nmol/cm2/hr or ~4 metric tons/km2/yr, more than double the average of 1.5 tons P/km2/yr for the North IRL. The vertical profile for dissolved sulfide (Figure 3.10B) shows that dissolved sulfide concentrations peaked at ~3,000 µM (~96 mg S/L). Sulfide also is diffusing out from sediments to the overlying water in Turkey Creek. We have added a significant sediment flux program to our proposed 2016 Turkey Creek effort and will be carrying out flux studies at five sites in Turkey Creek before and after dredging.

(A) + (B) NH4 (M) Sulfide (M) 0 500 1000 1500 0 1000 2000 3000 4000

Bottom Water = 5.2M Bottom Water = <0.5 M 0 0

10 10

20 20

Station TC5 Temp = 30°C Station TC5 Sediment Depth (cm) Sediment Depth (cm) 30 30 TC5A TC5A TC5B TC5B Bottom water 40 40

Figure 3.10. Vertical profiles for (A) dissolved ammonium and (B) dissolved sulfide in sediment interstitial water at station TC5 on May 5, 2015 (location shown on Figure 3.1).

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3.4.3 Water Quality Surveys

3.4.3.1 Overview

Monthly water quality surveys were carried out at five locations in Turkey Creek and the adjacent IRL (Figure 3.11) from April through December, 2015. Stations TC1, TC2 and TC3 were located at water depths of 1.1-2.2 m; stations TC4 and TC5 were situated in small depressions (water depths >3m) to the east (TC4) and west (TC5) of US1 (Figure 3.11). The complete data set is presented in Appendix C. Both molar and mass/volume units are used for water quality parameters in tables, figures and appendices. Data in the text are presented in molar units with the occasional addition of mass/volume units in parentheses. Salinity values are dimensionless because the Practical Salinity Scale is based on a ratio, not a concentration (e.g., Millero, 2006).

The following brief overview of our complete data set for water quality precedes a more detailed discussion of parameters that will be used to assess post-dredging conditions (Table 3.5). Over the nine-month period, the freshest water was at the surface in Turkey Creek during July (S = 0.64 at

TC1 (2.2 m)

TC2 (1.7 m)

TC3, (1.1 m)

TC4 (3.4 m)

TC5 (3.0 m)

Figure 3.11. Locations of water quality stations TC1-TC5 with average water depths at each station and contour lines for muck thicknesses from our February 2015 survey.

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Table 3.5. Summary of 2015 data from (A) continuous profiles obtained using a YSI Sonde 6600 and (B) 135 discrete water samples (15/month). The text in parentheses for maximum (max) and minimum (min) values gives station identification, water depth and month sampled.

(A) DO Salinity Temp (˚C) DO (% sat) pH 2015 (mg/L) Mean 19.4 27.6 59 4.8 7.75 SDa 5.6 3.1 26 6.3 0.35 Max 28.3 32.7 100 7.7 8.33 (TC1, 1.8 m Jul) (TC4, 0.5 m Aug) (TC1, May, Sep) (TC1, 2m Dec) (TC1, 2 m Dec) Min 0.64 22.6 <3 <0.2 7.01 (TC5, 0.5 m Jul) (TC5, 2.8 m Dec) (TC5, 2.5 m Aug) (TC5, 2.5 m Aug) (TC4, 3.2 m Apr) Median 18.8 28.1 64 4.6 7.80

NH + NH + Nitrate Nitrate Total Total PO 3- PO 3- Total Total P (B) 4 4 4 4 (µM) (mg N/L) Nitrite Nitrite Dis. N Dis. N (µM) (mgP/L) P (mgP/L) 2015 (µM) (mgN/L) (µM) (mgN/L) (µM) Mean 7.8 0.109 0.9 0.0126 54.6 0.76 1.27 0.0393 2.00 0.062 SDa 10.5 0.147 1.3 0.0182 21.5 0.30 1.74 0.0539 1.69 0.052 Max 64.7 0.906 7.9 0.1110 168 2.35 9.97 0.309 9.8 0.304 (TC4, 3 m Sep) (TC5, 2.8 m Nov) (TC4, 3 m Aug) (TC5, 2.5 m Aug) (TC5, 2.5 m Aug) Min 2.1 0.029 0.1 0.0014 21.4 0.30 0.03 0.001 0.54 0.017 (TC4, 0.5 m Oct) (TC4, 3 m Aug) (TC4, 1 m Apr) (TC1, 0.5 m Dec) (TC1, 1.5 m Jun) Median 4.6 0.064 0.5 0.0070 47.6 0.67 0.8 0.0248 1.5 0.046 aSD = standard deviation.

station TC5). The highest salinity water was in the IRL during July (S = 28.3 at station TC1), just prior to a large increase in runoff to the IRL from Turkey Creek. Water temperatures ranged from 22.6-32.7˚C with highest temperatures in August and lowest temperatures in December (Table 3.5). Temperatures in the open IRL (station TC1) averaged ~1.6 ± 0.7˚C lower than in the creek during all months except July-September when water temperatures in the lagoon averaged ~0.87 ± 0.06˚C lower than in the creeks (Appendix C). Highest concentrations and saturation values for dissolved oxygen were found in the IRL (station TC1) throughout the year (Table 3.5, Appendix C). Bottom water in both small depressions (stations TC4 and TC5) became anoxic during July-August with persistence into September (Table 3.5, Appendix C). Overall, average concentrations of ammonium were ~9 times greater than nitrate + nitrite, yet these three forms of dissolved inorganic N accounted for an average of only ~15% of the total dissolved N (Table 3.5). The dominant form of dissolved nitrogen was dissolved organic nitrogen (DON) as previously reported for Turkey Creek (e.g., Dierberg, 1991) and the IRL (e.g., Lapointe et al., 2015). In contrast, on average, phosphate made up ~60% of the total dissolved P. Highest concentrations of ammonium, total dissolved N, phosphate, and total dissolved P were found in the bottom water at stations TC4 and TC5 during August-September (Table 3.5). These high values are linked to releases from muck sediments as discussed below. The highest concentration of nitrate + nitrite also was found in the deeper depression at station TC5 during November, most likely from nitrification of ammonia that

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was released from the sediments and oxidized when oxygen levels in this basin increased during November and December (Table 3.5, Appendix C). Average and highest values for phosphate were greater than those for nitrate + nitrite, but not ammonium (Table 3.5).

3.4.3.2 Water Quality in the IRL (Station TC1) versus Turkey Creek (Station TC5): Dissolved Components

Dredging in Turkey Creek will likely have some effect on water quality in both the creek and adjacent lagoon. Our nine-month study of five water quality stations covers several different areas including (1) the more restricted area between the FEC railroad bridge and U.S. Route 1 in Turkey Creek (station TC5), (2) the bay area of Turkey Creek east of U.S. Route 1 (stations TC2-4) and (3) the adjacent IRL (station TC1). To show the pre-dredging water quality across the area, we will compare water quality for station TC1 in the IRL with station TC5 between US1 and the FEC railroad bridge. These two stations represent the IRL and Turkey Creek water masses that mix across the area to be dredged.

Salinities in bottom water (1-2.5 m) at station TC1 ranged from ~16 (Sep-Nov) to ~28 in July (Figure 3.12). In contrast, at station TC5, bottom water (1.5-3.2 m) salinities were in narrow ranges of ~17-19 from July-December and ~23-25 for April-June (Figure 3.13). Surface water at station TC1 ranged from 10-26 with the higher salinities from April-July before the onset of heavy rainfall during September-October (Figure 3.12). In contrast, surface water salinities at station TC5 ranged from 0.6-4 for eight of the nine months (Figure 3.13). These expected salinity differences emphasize the distinction between the western and eastern reaches of the study area. Temperatures at station TC1 were within ≤2˚C of those at station TC5 during all sampling periods with highest temperatures at both stations in August (32-33˚C) and lowest temperatures (22-23˚C) in December (Figures 3.12 and 3.13). Temperature does not greatly differentiate the water masses across the study area.

Oxygen saturation was consistently higher at station TC1 than TC5 (Figures 3.12 and 3.13). For example, the lowest degree of oxygen saturation at station TC1 was 50-60% during July- September whereas bottom water oxygen saturation at station TC5 was <50% for every month except December with 80% saturation (Figure 3.13). Furthermore, water at station TC5 ranged from nearly anoxic to only ~20% saturation during April and from August to October (Figure 3.13). The observed differences in oxygen levels at the two stations corresponded with large differences in concentrations of inorganic nutrients as described below.

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(A) Salinity (B) Temperature (C)

10 15 20 25 30 22 24 26 28 30 32 0.0 0.0 6 9 0.5 8 4 0.5

1.0 1.0

1.5 1.5 12 7 7 6 5 5 4 2.0 10 2.0 12 10 8 11 11 9 2.5 Bottom 2.5 Bottom Water Depth (m) Water Depth (m) Water Depth 3.0 Station TC1 3.0 Station TC1 3.5 2015 3.5 2015

4.0 4.0 (C) DO (% Saturation) (D) TSS (mg/L) 40 50 60 70 80 90 100 0 5 10 15 20 25 30 0.0 0.0 Apr May 0.5 0.5 Jun 6 Jul 1.0 1.0 Aug Sep Oct 1.5 1.5 Nov 7 8 Dec 4 12 2.0 5 2.0 9 10 11 Bottom 2.5 Bottom 2.5 Water Depth (m) Water Depth (m) Water Depth 3.0 3.0 Station TC1 Station TC1 2015 2015 3.5 3.5

4.0 4.0

Figure 3.12. Vertical profiles for (A) salinity, (B) temperature, (C) % oxygen saturation and (D) total suspended solids (TSS) for station TC1 in Turkey Creek for monthly surveys from April- December 2015. Numbers on A, B and C refer to the number of month when profile was obtained.

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(B) Temperature (C) (A) Salinity 0 5 10 15 20 25 0.0 22 24 26 28 30 32 4 0.0 5 12 0.5 0.5 6 1.0 1.0 9 8 1.5 1.5

2.0 2.0

6 2.5 Station TC5 2.5 8 Water (m) Depth Water Depth (m) 2015 4 9 3.0 12 3.0 10 11 11 5 10 Bottom 3.5 Bottom 3.5 Station TC5, 2015 4.0 4.0 (C) DO (% Saturation) (D) TSS (mg/L) 0 5 10 15 20 25 30 0 20406080100 0.0 0.0 10 Apr 0.5 May 0.5 Station TC5 Jun 2015 Jul 1.0 Aug 1.0 Sep 1.5 Oct 1.5 6 Nov 8 Dec 2.0 4 2.0

2.5 2.5 9 Water Depth (m) Water Depth Water Depth (m) 5 3.0 12 3.0 11 Bottom 3.5 Bottom 3.5 Station TC5, 2015 4.0 4.0

Figure 3.13. Vertical profiles for (A) salinity, (B) temperature, (C) % oxygen saturation and (D) total suspended solids (TSS) for station TC5 in Turkey Creek for monthly surveys from April-December 2015. Numbers on A, B and C refer to the number of month when profile was obtained.

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Concentrations of TSS at station TC1 were <5 mg/L during April-June with a peak value of 18.5 mg/L in bottom water during a windy period in November (Figure 3.12). Values for TSS at station TC5 were in the range of ~2-10 mg/L as at station TC1 with the exception of values of 13-18 mg/L in bottom water at station TC5 during a period of swift currents in December (Figure 3.13).

Concentrations of dissolved ammonium at station TC1 were 6- to 30-fold greater than concentrations of nitrate + nitrite during all months except November when ammonium enrichment was only 1.3- to 3.3-fold greater than nitrate + nitrite (Figure 3.14). Vertical profiles for ammonium and nitrate + nitrite at station TC1 were relatively uniform during each sampling period due to active mixing in these 2-m deep lagoon waters (Figure 3.14). Trends for ammonium and nitrate + nitrite were greatly different at station TC5 (Figure 3.15). In the upper 1 m at station TC5, concentrations of ammonium were <10 µM (<0.14 mg N/L) as found throughout the water column at station TC1 (Figures 3.14 and 3.15). In contrast, concentrations of ammonium in the bottom meter of water at station TC5 were very high at 20-50 µM during August, September and December (Figure 3.15). These elevated ammonium concentrations in bottom water resulted from releases of nitrogen (99% as ammonium) from the sediment interstitial water as discussed above (Section 3.4.2 and Figure 3.10A).

We used our flux data for station TC5 to help validate the statement that sediments are a key source of ammonium to the creek system. The previously noted ammonium flux during June of ~12 2 2 + nmol/cm /hr (~15 tons N/km /yr) from sediments at station TC5 releases 288 nmol NH4 in 24 hours to 0.1 L of water (1 cm2 x 100 cm depth of bottom water = 100 cm3 = 0.1 L) to yield a water column ammonium concentration of ~2.9 µM (0.288 nmol/0.1 L). Ammonium concentrations in the bottom meter of water at station TC5 were 12 µM in May and 50 µM in August (Figure 3.15). It would take only ~4 days to add enough ammonium to reach the May value of 12 µM and ~17 days to yield a bottom water ammonium value of 50 µM obtained in August. Bottom water at station TC5 seems quite stagnant over the summer when concentrations of both ammonium and hydrogen sulfide became quite high. This calculation confirms the importance of muck as an important source of dissolved N to Turkey Creek and the IRL. Our ongoing work on the Algal Bloom Investigation and plans for more flux and water quality measurements in Turkey Creek should continue to improve the link between muck and excessive productivity in the IRL.

Concentrations of dissolved nitrate + nitrite were high in the surface water at station TC5 during September, October, November and December (Figure 3.15B) due to freshwater runoff from Turkey Creek (Figure 3.13A shows salinity). The highest concentrations of nitrate + nitrite during the 9 months (Table 3.7) were observed in bottom water at station TC5 during October and November (Figure 3.15B). This enrichment of nitrate + nitrite most likely resulted from partial nitrification of the large inventory of ammonium present during August and September (Figures

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- - (A) + (B) NO + NO NH4 (M) 3 2 (M) 02468101214 0246810 0.0 0.0 Apr Apr May May 0.5 0.5 Jun Jun Jul Jul 1.0 Aug 1.0 Aug Sep Sep Oct Oct 1.5 1.5 Nov Nov Dec Dec 2.0 2.0 Bottom Bottom 2.5 2.5 Water Depth (m) Water Depth (m) 3.0 Station TC1 3.0 Station TC1 2015 2015 3.5 3.5

4.0 4.0 0.0 0.1 0.2 0.0 0.07 0.14 NH + (mg N/L) NO - + NO - (mg N/L) 4 3 2

(C) Total Dissolved N (M) (D) DOC (mM) 0 20406080100 0.0 0.5 1.0 1.5 2.0 0.0 0.0 Apr Apr May 0.5 May 0.5 Jun Jun Jul Jul 1.0 1.0 Aug Aug Sep Sep Oct 1.5 Oct 1.5 Nov Nov Dec 2.0 Dec 2.0 Bottom Bottom 2.5 2.5 Water Depth (m) Water Depth Water Depth (m) 3.0 Station TC1 3.0 Station TC1 2015 2015 3.5 3.5

4.0 4.0 0.0 0.7 1.4 0.0 12.0 24.0 Total Dissolved N (mg/L) DOC (mg/L)

Figure 3.14. Vertical profiles for (A) dissolved ammonium, (B) dissolved nitrate + nitrite, (C) total dissolved nitrogen and (D) dissolved organic carbon (DOC) for station TC1 in Turkey Creek for nine monthly surveys from April-December 2015.

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(A) + (B) NO - + NO - (M) NH4 (M) 3 2 0 1020304050 0246810 0.0 0.0 Apr May 0.5 Jun 0.5 Jul Apr 1.0 Aug 1.0 May Sep Jun Oct Jul 1.5 Nov 1.5 Aug Dec Sep 2.0 2.0 Oct Nov Dec 2.5 2.5 Water Depth (m) Water Depth (m) Depth Water 3.0 3.0 Bottom Bottom 3.5 Station TC5 3.5 Station TC5 2015 2015 4.0 4.0 0.0 0.07 0.14 0.0 0.35 0.7 - - NO3 + NO2 (mg N/L) NH + (mg N/L) 4 (C) Total Dissolved N (M) (D) DOC (mM) 050100150200 0.0 0.5 1.0 1.5 2.0 0.0 0.0 Apr Apr May May 0.5 0.5 Jun Jun Jul Jul Aug 1.0 Aug 1.0 Sep Sep Oct Oct 1.5 1.5 Nov Nov Dec Dec 2.0 2.0

2.5 2.5 Water Depth (m) Water Depth Water Depth (m) 3.0 3.0 Bottom Bottom 3.5 Station TC5 3.5 Station TC5 2015 2015 4.0 4.0 0.0 1.4 2.8 0.0 12.0 24.0 Total Dissolved N (mg/L) DOC (mg/L)

Figure 3.15. Vertical profiles for (A) dissolved ammonium, (B) dissolved nitrate + nitrite, (C) total dissolved nitrogen and (D) dissolved organic carbon (DOC) for station TC5 in Turkey Creek for nine monthly surveys from April-December 2015.

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3.15A, B). Increased oxygen in the bottom water during late fall must have been sufficient to promote bacterial oxidization of ammonium to nitrite and nitrate (Figures 3.13C and 3.15B).

Vertical profiles for total dissolved nitrogen, which includes ammonium, nitrate + nitrite, and dissolved organic nitrogen (DON) are generally uniform within a given sampling period. Values for DON at station TC1 for April-October (40 ± 10 µM) increased to ~60-70 µM (~0.84-0.98 mg N/L) during November and December. At station TC5, concentrations of total dissolved nitrogen were 30-70 µM and uniform with depth during most months; a sharp increase in values in the bottom water during August and December was caused by increased ammonium concentrations.

Vertical profiles for phosphate at station TC1 show uniform distribution during each survey with a 20-fold range in values from 0.05 µM (~1.5 µg P/L) in December to 1.1 µM (~34 µg/ P/L) in October (Figure 3.16A). Vertical trends for total dissolved phosphorus were similar to those for phosphate at station TC1 with about a 3-fold range in values from a low of 0.56 µM in December to 1.0 µM in October (Figure 3.16B). Phosphate made up only ~10% of the total dissolved phosphorus in December and ~58% in October. Yet, concentrations of dissolved organic phosphorus (DOP = TDP – SRP) for December (0.5 µM) and October (0.8 µM) were more similar. The lowest concentration of phosphate at station TC5 (0.8 µM in July) was 16 times higher than the lowest value at station TC1. Likewise, the highest phosphate value at station TC5 (10 µM in October) was ~9 times higher than the highest concentration of phosphate at TC1 (1.1 µM). These differences are most likely related to release of phosphate from muck in Turkey Creek. Values for DOP at station TC5 (0.3 µM) averaged half the values for station TC1.

Most of the vertical and seasonal trends observed for nutrients at station TC1 also were observed at stations TC2 and TC3 (Appendix C). Likewise, vertical and seasonal trends discussed for station TC5 also were observed at station TC4 (Appendix C). Stratification was more pronounced at station TC5 than at station TC4 where a thicker surface layer of fresher, cooler water was observed. Concentrations of dissolved ammonium in bottom water at station TC5 were 20-50% lower than at station TC4; however, the layer of ammonium-rich bottom water at station TC5 was at least twice as thick as at station TC4. Concentrations of dissolved phosphate in bottom water at station TC 5 were lower and less uniform than observed at station TC 4. The dissolved parameters in the water quality data set for Turkey Creek tell a rich spatial and seasonal story, one that should provide a solid framework for comparison with post-dredging results.

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PO 3- (M) 4 Total Dissolved P (M) 012 0123 0.0 0.0 Apr Apr May 0.5 May Jun 0.5 Jun Jul Jul 1.0 Aug 1.0 Aug Sep Sep 1.5 Oct 1.5 Oct Nov Nov Dec Dec 2.0 2.0 Bottom Bottom 2.5 2.5 Water Depth (m) Water Depth Water Depth (m) Depth Water 3.0 Station TC1 3.0 Station TC1 2015 2015 3.5 3.5

4.0 4.0 0.0 0.04 0.08 0.0 0.05 0.10 PO 3- (mg P/L) 4 Total Dissolved P (mg/L)

3- PO4 (M) Total Dissolved P (M) 0246810 0246810 0.0 0.0 Apr Apr May May 0.5 Jun 0.5 Jun Jul Jul 1.0 Aug 1.0 Aug Sep Sep Oct Oct 1.5 Nov 1.5 Nov Dec Dec 2.0 2.0

2.5 2.5 Water Depth (m) Depth Water Water Depth (m) 3.0 3.0 Bottom Bottom 3.5 Station TC5 3.5 Station TC5 2015 2015 4.0 4.0 0.0 0.15 0.3 0.0 0.15 0.3 PO 3- (mg P/L) 4 Total Dissolved P (mg/L)

3- Figure 3.16. Vertical profiles for (A) dissolved phosphate (PO4 ) and (B) total dissolved phosphorus at station TC1, and (C) dissolved phosphate and (D) total dissolved phosphorus at station TC5 (with scale change for x- axis) in Turkey Creek for nine monthly surveys from April-December 2015.

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3.4.3.3 Water Quality in the IRL (Station TC1) versus Turkey Creek (Station TC5): Particulate Components

A strong linear relationship was observed for turbidity (in nephelometric turbidity units, NTU) versus TSS (Figure 3.17A). The slope of the line (0.46) is consistent with a previous slope of 0.44 for results from the Indian River Lagoon System by Trefry et al. (2007, Figure 3.17B). Thus, TSS concentrations (in mg/L) are about twice the turbidity values (in NTU). Four samples collected during 2015 from water depths of 2-3 m at stations TC4 and TC5 showed deviations from the expected trend (Figure 3.17A), deviations that had not previously been seen by us in the IRL (e.g., Trefry et al., 2007). The sample that plotted below the lower prediction interval on Figure 3.17A appeared to be very fine-grained on the filter and contained a very high POC of 44%. Based on previous discussion about the carbon content of typical organic matter in the marine environment, the sample with 44% carbon contained 11% N and had a low C/N atomic ratio of 4.8, not uncommon for bacteria (Zimmerman et al., 2014). In contrast, the three samples with data that plotted above the upper confidence limit on Figure 3.17A averaged ~33% organic C and 6.0% organic nitrogen. These other anomalies also are possibly linked to a local source of organic matter.

(A) (B) 20 Turkey Creek 2015 MB Y = 0.44X + 1.33 30 3m TC4 Sep VB r = 0.95, n = 95, p<0.001 3m TC4 Oct 15 BR TB ML 20 10 2.5m TC5 Aug 10 Y = 0.46(X) + 0.93

r = 0.91, n = 136, p<0.001 Turbidity (NTU) 5 Turbidity (NTU) 2 m TC4 Apr Trefry et al. (2007) 0 0 0 102030405060 0 5 10 15 20 25 30 Total Suspended Solids (mg/L) Total Suspended Solids (mg/L)

Figure 3.17. (A) Turbidity (in nephelometric turbidity units, NTU) versus total suspended solids TSS), (B) Turbidity versus TSS from Trefry et al. (2007) for samples from the Indian River Lagoon System (MB = Melbourne, VB = Vero Beach, BR = Banana River Lagoon, TB = Turnbull Creek area, ML = Mosquito Lagoon). Solid lines and equation are from linear regression analysis, dashed lines show 95% prediction interval. Anomalous data points are identified by water depth, location and month during 2015.

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As previously discussed, the organic matter (% OM) content of the suspended matter was ~3 times the % TOC value (% OM = 0.35 POC + 0.8, Figure 3.7A). Therefore, the suspended matter from station TC1 ranges from ~30% OM (POC = 10%) to essentially 100% OM (POC = 35%) with an average of ~60% OM (POC data on plotted Figure 3.18). Suspended matter from station TC5 is more organic rich with an average closer to 80% OM. While sampling at station TC5, observable plant debris was regularly floating by us in the surface water. Concentrations of POC were inversely correlated with Al (Figure 3.20A) where Al is a proxy for clay mineral (aluminosilicate) content. The x-intercept on Figure 3.20A is at ~5% Al and represents 100% aluminosilicates and 0% organic matter. At POC = 20%, the Al content is ~2%, and thus the sample is ~60% OM and 40% aluminosilicate. Using this designation for the organic and inorganic content of the suspended matter, we can track changes in both the amount (TSS) and composition of the suspended matter after dredging.

The suspended matter at station TC1 contained a lower range of values for total particulate N and P than found at station TC5, consistent with the trend for more organic-rich particles at station TC5 (Figures 3.18 and 3.19). The particulate (C/N) atomic ratio averaged ~6.2 (Figure 3.20B and Appendix C) for the pre-dredge samples and is in reasonable agreement with Redfield ratio (C/N = 6.6). Anomalous total particulate P values were found in bottom water at stations TC 4 and 5 and high total particulate Fe values were observed in surface water at stations TC4 and 5. Iron is flowing in with creek water and the Fe is likely precipitating as an Fe (III) oxide with a positive charge and possibly scavenging negatively-charge phosphate ions from the water column to increase P concentrations in suspended and bottom sediments (e.g., Gunnars et al., 2002). Within this large data set for particles, we have a wide selection of biogeochemical tools to help explain changes that occur after dredging.

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TSS (mg/L) POC (%) 0 5 10 15 20 25 30 0 1020304050 0.0 0.0 Apr Apr May May 0.5 Jun 0.5 Jun Jul Jul 1.0 Aug 1.0 Aug Sep Sep Oct Oct 1.5 Nov 1.5 Nov Dec Dec 2.0 2.0 Bottom Bottom 2.5 2.5 Water Depth (m) Water Depth (m) Depth Water 3.0 Station TC1 3.0 Station TC1 2015 2015 3.5 3.5

4.0 4.0 PON (%) Total Particulate P (%) 0246810 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.0 Apr Apr May May 0.5 Jun 0.5 Jun Jul Jul 1.0 Aug 1.0 Aug Sep Sep Oct Oct 1.5 Nov 1.5 Nov Dec Dec 2.0 2.0 Bottom Bottom 2.5 2.5 Water Depth (m) Depth Water Water Depth (m) 3.0 Station TC1 3.0 Station TC1 2015 2015 3.5 3.5

4.0 4.0

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TSS (mg/L) POC (%) 0 5 10 15 20 25 30 0 102030405060 0.0 0.0 Apr Apr 0.5 May May Jun 0.5 Jun Jul Jul 1.0 Aug 1.0 Aug Sep Sep 1.5 Oct Oct Nov 1.5 Nov Dec Dec 2.0 2.0

2.5 2.5 Water Depth (m) Depth Water Water Depth (m) Water Depth 3.0 3.0 Bottom Bottom 3.5 Station TC5 3.5 Station TC5 2015 2015 4.0 4.0

PON (%) Total Particulate P (%) 02468101214 0.00.51.01.52.0 0.0 0.0 Apr Apr May 0.5 0.5 May Jun Jun Jul Jul 1.0 Aug 1.0 Aug Sep Sep 1.5 Oct 1.5 Oct Nov Nov Dec Dec 2.0 2.0

2.5 2.5 Water Depth (m) Water Depth (m) Depth Water 3.0 3.0 Bottom Bottom 3.5 Station TC5 3.5 Station TC5 2015 2015 4.0 4.0

Figure 3.19. Vertical profiles for (A) total suspended solids (TSS), (B) particulate organic carbon (POC), (C) particulate organic nitrogen (PON), and (D) total particulate phosphorus at station TC5 in Turkey Creek for nine monthly surveys from April-December 2015.

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(A) (B) 50 12 Turkey Creek 2015 Turkey Creek 2015 2m TC4 Apr 40 8 30

20 POC (%) 4

10 Y = 0.17 X + 0.38 Y = -7.5(X) + 36.7 r = 0.89, n = 135, p<0.001

r = 0.79, n = 109, p<0.001 (%) N Particulate Total 0 0 012345 0 1020304050 Al (%) POC (%)

(C) (D) 2.0 10 Y = 0.026(X) + 0.013 Turkey Creek 2015 r = 0.89, n = 127, p<0.001 8 0.5m TC5 Dec 1.5 0.5m TC5 Oct 1m TC5 Sep 0.5m TC5 Sep 0.5m TC5 Jun 2.5m TC5 Sep 6 TC5 Jun 0.5 m TC5 Apr 0.5 m TC5 Nov 1.0 3m TC4 Jun 0.5 m TC5 Aug 0.5 m TC5 Nov 2m TC5 Jun 4 0.5 m TC5 May 2m 2.5 m TC5 Apr TC4 Apr 0.5 2 Turkey Creek 2015 Particulate Fe (%) Y = 0.84X - 0.47 r = 0.83, n = 125, p<0.001 Total Paarticulate P (%) 0.0 0 0 1020304050 0123456 POC (%) Particulate Al (%)

Figure 3.20. (A) Particulate organic carbon (POC) versus aluminum (Al), (B) total particulate nitrogen versus POC, (C) total particulate phosphorus versus POC and (D) total particulate iron versus total particulate Al. Solid lines and equation are from linear regression analysis, dashed lines show 95% prediction interval. Anomalous data points are identified by water depth, location and month during 2015.

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3.4.4 Chemical Forms of Dissolved and Particulate Nitrogen and Phosphorus

The growth of algae and phytoplankton generally depends on the dissolved inorganic forms of nitrogen (ammonium, nitrate, and nitrite) and phosphorus (phosphate). In some instances, simple organic molecules such as urea (CH4N2O) or methylphosphonic acid [CH3P(OH)2] may be used by primary producers as sources of dissolved nitrogen and phosphorus (e.g., Kudo et al., 2015; Van Mooy et al., 2015). For this study, the pre-dredge data for the various forms of nitrogen and phosphorus provide another point of reference to assess post-dredging results.

The most abundant form of nitrogen in the water column in Turkey Creek and the adjacent IRL was DON with an average of 46 ± 14 µM (0.64 ± 0.20 mg N/L, Table 3.6) that accounted for an average of 58 ± 11% of the total nitrogen in the water column (Table 3.7 and Figure 3.21). Dierberg (1991) reported an average DON value of 47 ± 11 µM (0.66 ± 0.15 mg N/L) for Turkey Creek during normal flow in 1988 and 1989; these values were not statistically different from our results for 2015 (Table 3.6).

Particulate N, the fraction associated with suspended sediments, made up an average of 32 ± 12% of the total nitrogen in our water samples (Table 3.7 and Figure 3.21). In contrast, Dierberg (1999) found very low concentrations for particulate N during normal flow in the creek because concentrations of suspended sediment upstream were low (Table 3.6). Dierberg (1991) found particulate N values closer to our values for Turkey Creek and the adjacent IRL during storm flow (Table 3.9). The fine-grained, organic-rich sediment east of the FEC railroad bridge is easily resuspended and regularly yields higher values for particulate N in the lower creek than during non-storm periods in upstream waters.

Ammonium was the most abundant form of dissolved inorganic N found in our study area and was present at an average of ~9 times greater than nitrate + nitrite (Tables 3.8). Dierberg (1991) reported higher nitrate + nitrite values than ammonium concentrations for upstream in Turkey Creek. We know that the area between the FEC railroad bridge and the mouth of Turkey Creek receives a large flux of ammonium from the muck sediments that likely shifts the + - - [ammonium/(nitrate + nitrite)] ratio in favor or ammonium. The average [NH4 ]/[NO3 + NO2 ] was ~20 with a range of 0.77 to 480 (Appendix C).

When just the soluble forms of nitrogen are considered, DON makes up 40-95% of the total dissolved nitrogen (Table 3.10). This predominance of DON is a common observation for estuaries and creeks in Florida, including Turkey Creek (e.g., Dierberg, 1991; Lapointe et al., 2015). Higher concentrations of ammonium than nitrate + nitrite help support the importance of muck sediments as a source of dissolved nitrogen to Turkey Creek and the adjacent IRL. The dissolved nitrogen in muck is >99% ammonium with concentrations as high as 3000 µM (42 mg N/L).

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Table 3.6. Concentrations of the various forms of nitrogen in the water column of Turkey Creek and the adjacent IRL. Dates and locations of maxima and minima are shown in [ ]. Units are µM and {mg N/L}.

Parameter Ammonium Nitrate-nitrite DON1 Particulate N 2015 (µM) {mg N/L} (µM) {mg/L} (µM) {mg/L} (µM) {mg/L} This study Mean 8.0 {0.11} 0.93 {0.013} 46.1 {0.64} 28.2 {0.39} Std. Dev 10.5 {0.17} 1.27 {0.018} 14.2 {0.20} 22.2 {0.31} Max 64.7 {0.91} 7.91 {0.111} 105 {1.5} 224 {3.1} [TC4, 3 m Sep] [TC5, 2.8 m Nov] [TC4, 3 m Aug] [TC4, 2 m Apr] Min 2.2 {0.031} 0.13 {0.002} 17 {0.24} 6.3 {0.09} [TC1, 0.5 m Jul] [TC4, 3 m Aug] [TC1, 1 m Apr] [TC5, 0.5 m Oct.] Turkey Creek normal flow (Dierberg, 1991) Mean 1.9 {0.026} 4.6 {0.065} 47.1 {0.66} 2.9 {0.04} Std Dev 1.1 {0.016} 4.8 {0.067} 10.7 {0.15} 2.1 {0.03} Turkey Creek storm flow (Dierberg, 1991) Maximum 14.3 {0.2} 17.9 {0.25} 71 {1.0} 21 {0.3} 1DON = Dissolved Organic Nitrogen.

Table 3.7. Percentages of the various forms of nitrogen in the waters of Turkey Creek and the adjacent IRL.

Parameter Ammonium Nitrate-nitrite DON1 Particulate N (%) (%) (%) (%) Mean 8.9 1.2 57.8 32.1 Std. Dev 7.2 1.7 10.5 12.0 Max 42.2 9.5 79.5 80.5 [TC4, 3 m Sep] [TC4, 0.5 m Nov] [TC1, 0.5 m Jun] [TC4, 2 m Apr] Min 2.0 0.07 17.2 9.6 [TC4, 2 m Apr] [TC4, 3 m Aug] [TC4, 2 m Apr] [TC5, 0.5 m Oct] 1DON = Dissolved Organic Nitrogen.

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Nitrate + Nitrite 1.2%

Dissolved Organic Nitrogen 57.8%

Ammonium 8.9%

Particulate Nitrogen 32.1%

Figure 3.21. Pie diagram showing the percentages of the different chemical forms of nitrogen in the waters of Turkey Creek and the adjacent Indian River Lagoon.

Table 3.8. Percentages of the various forms of dissolved nitrogen in the waters of Turkey Creek and the adjacent IRL.

Parameter Ammonium Nitrate-nitrite Dissolved (%) (%) Organic N (%) Mean 12.6 1.7 85.7 Std. Dev 9.1 2.1 9.2 Max 56.1 12.7 94.7 [TC4, 3 m Sep] [TC5, 3 m Oct] [TC4, 2 m Oct] Min 4.4 0.08 43.8 [TC1, 0.5 m Nov] [TC4, 3 m Aug] [TC4, 3 m Sep]

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A more even distribution was found among the three forms of phosphorus (dissolved phosphate, DOP and particulate phosphorus) than nitrogen in the water column in our study area (Figure 3.22). Our values for dissolved phosphate are higher and more variable than reported by Dierberg (1991; Table 3.9). We look forward to upstream sampling during 2016 to determine whether the higher phosphate values in Turkey Creek and the adjacent IRL are linked to increased concentrations upstream or to release of dissolved phosphate from muck. As was the case for dissolved nitrogen, the highest concentrations of dissolved phosphate and DOP were found in deeper water at stations TC4 and TC5 (Table 3.9). Lower DOP values were found at stations TC1 and TC2 (Table 3.9). In contrast with nitrogen, the percent abundance of DOP at 29% was lower than the DON value of 60% (Tables 3.10 and 3.7). The dissolved forms of phosphorus, phosphate and DOP, each made up about half of the soluble phosphorus (Table 3.11).

Dissolved Phosphate 29.7% Dissolved Organic Phosphorus 21.6%

Particulate Phosphorus 48.7%

Figure 3.22. Pie diagram showing the percentages of the different chemical forms of phosphorus in the waters of Turkey Creek and the adjacent Indian River Lagoon.

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Table 3.9. Concentrations of the various forms of phosphorus in the water column of Turkey Creek and the adjacent IRL. Parameter Phosphate Dissolved Particulate P (µM) {mg/L} Organic P (mg/L) (mg/L) This Study Mean 1.27 {0.039} 0.69 {0.021} 1.67 {0.052} Std. Dev 1.74 {0.054} 0.38 {0.012} 0.95 {0.029} Max 9.97 {0.309} 2.3 {0.071} 6.3 {0.195} [TC5, 2.5 m Aug] [TC5, 2.5 m Jun] [TC4, 2 m Apr] Min (0.03) {0.001} <0.2 {<0.004} 0.31 {0.010} [TC1, 0.5 m Dec] [TC5, 2.5 m Aug] [TC1, 1 m Jun] Turkey Creek normal flow (Dierberg, 1991) Mean 0.64 {0.020} 1.6 {0.05} 0.42 {0.013} Std Dev 0.34 {0.011} 0.32 {0.01} 0.32 {0.010}

Table 3.10. Percentages of the various forms of phosphorus in the waters of Turkey Creek and the adjacent IRL.

Parameter Phosphate (%) Dissolved Particulate P Organic P (%) (%)

Mean 29.7 21.6 48.7 Std. Dev 19.5 14.2 17.2 Max 86.1 49.2 97.6 [TC5, 2.5 m Aug] [TC1, 1.75 m May] [ TC3, 0.9 m May] Min 4.6 <1 15.4 [TC5, 0.9 m May] [TC4, 3 m Aug] [TC5, 2.5 m Apr]

Table 3.11. Percentages of the various forms of dissolved phosphorus in the waters of Turkey Creek and the adjacent IRL.

Parameter Phosphate (%) Dissolved Organic P (%) Mean 52.4 47.6 Std. Dev 23.4 23.4 Max 100 94 [TC4, 3 m Aug] [TC1, 0.5 m Dec] Min 6 <1 [TC1, 0.5 m Dec] [TC4, 3 m Aug]

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3.5 Conclusions

The conclusions from this study are presented as a series of bulleted items with supporting references to figures, tables and text from this section (3) of the report. Results from a few very preliminary calculations are included to provide a quantitative context and starting point for answering a variety of research and management questions.

(1) Muck with thicknesses >25 cm covers ~50% of the area of Turkey Creek studied.

Based on Figure 3.3 and Table 3.2 that show ≥25 cm of muck in ~100 of ~200 grids (see Appendix A). With a grid size of ~800 m2, the area with muck is ~80,000 m2.

(2) Present water depths in Turkey Creek will likely increase by 1-3 m after dredging.

Figure 3.4B.

(3) Turkey Creek muck contains >90% water by volume (>75% water by weight), 70-90% silt + clay, 10-20% organic matter with 0.4 to >0.8% N and 0.1-0.16% P.

Tables 3.3 and 3.4 and Appendix C.

(4) The masses of N and P in the muck sediments of Turkey Creek are estimated to be ≈600 metric tons of N and ≈130 metric tons of P.

Based on muck volume of 160,000 m3 (page 3-15, combined FIT and Brevard contractor) and the composition data listed above.

N = (160,000 m3) x (0.2 fraction solid sediment for 80% water) x (solid sediment density of 2.5 metric tons sediment/m3) x (0.006 is fraction N for 0.6% N) = 480 metric tons of N

Repeat for P with 0.13% P (0.0013 fraction P) = 104 metric tons P

(5) Fluxes of nitrogen (as ammonium) and phosphorus (as phosphate) are on the order of 20 and 4 metric ton/km2/yr to yield annual fluxes of N and P from sediments of 1.6 and 0.32 metric tons/yr, respectively.

Based on muck area of 80,000 m2 = 0.08 km2 (100 cells x 30 m x 28 m) N flux = (0.08 km2) x (20 metric tons N/km2/yr) = 1.6 metric tons N/yr = 1,600,000 g N/yr P flux = (0.08 km2) x (4 metric tons P/km2/yr) = 0.32 metric tons P/yr = 320,000 g P/yr

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(6) Vertical profiles for dissolved ammonium and phosphate show increased concentrations of 4- to >10-fold in the bottom water of shallow, low oxygen depressions during summer. These data provide direct evidence for the measurable impact of fluxes of N and P from sediments to the waters of Turkey Creek.

Average concentrations of ammonium and phosphate for the upper water column in Turkey Creek were 2-6 µM (0.03-0.08 mg N/L) and 0.2-1.5 µM (0.006-0.050 mg P/L), respectively. (Figures 3.14-16) Concentrations of ammonium and phosphate for shallow depressions in Turkey Creek during summer were ~8 µM (0.1 mg N/L) and ~1.3 (µM (0.04 mg P/L), respectively. (Figures 3.14-16)

(7) Releases of ammonium and phosphate from sediments as shown above would, if retained in the creek and not flushed to the IRL, hypothetically yield ammonium concentrations of ~5 mg N/L and 1 mg P/L relative to average values of 0.1 mg N/L and 0.04 mg P/L.

Volume of water in Turkey Creek study is 300,000 m3 {(80,000 m2 + 80,000 m2) x 1.8 m} or 300,000 m3 x 1000 L/m3 = 300 x 106 L. (Appendix A)

Ammonium from muck per year would yield a total concentration (if all was retained) of [(1,600,000 g/300 x 106 L)] = 0.0053 g/L = ~5 mg N/L.

Phosphate from muck per year would yield a total concentration (if all was retained) of [(320,000 g/300 x 106 L)] = 0.0011 g P/L = ~1 mg P/L.

(8) The average percentage of chemical forms of nitrogen in the waters of Turkey Creek and the adjacent IRL during 2015 were as follows: dissolved organic nitrogen (57.8%), ammonium (8.9%), nitrate + nitrite (1.2%) and particulate organic nitrogen (32.1%). The organic forms of N comprise ~90% of the total dissolved N in the water column.

The average chemical forms of phosphorus in the waters of Turkey Creek and the adjacent IRL were as follows: dissolved organic phosphorus (21.6%), phosphate (29.7%), and particulate organic phosphorus (48.7%). The organic forms of P comprise ~70% of the total dissolved P in the water column.

(9) The varied data set for muck and water in Turkey Creek obtained during 2015 offers several possible means for assessing the effectiveness of muck dredging including the following: (a) the amount of solid-phase N and P removed, (b) changes in concentrations of ammonium, phosphate, dissolved oxygen and other parameters in creek water and (c) decreases in the flux of N and P from sediments to overlying water of Turkey Creek.

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3.6 References

Barker, V. (2015) Natural Resources Management Director, Brevard County, Florida, personal communication.

Clesceri, S.L., Greenberg, E.A., Trussel, R.R. 1989. Standard Methods for the Examination of Water and Wastewater. 17th ed. Washington, D.C.: American Public Health Association, American Water Works Association, Water Pollution Control Federation.

Dierberg, F.E. 1991. Non-point source loadings of nutrients and dissolved organic carbon from an agricultural-suburban watershed in east central Florida. Water Research 4:363-374.

Folk, R. L. 1974. Petrology of Sedimentary Rocks. Hemphill Publishing Co., Austin, TX.

Garcia, D.A. (1998) The short-term impacts of dredging muck sediments from Crane Creek in Melbourne, Central Florida. M.S. Thesis, Florida Institute of Technology, 156 pp.

Gunnars, A., Blomqvist, S., Johansson, P., Andersson, C. 2002. Formation of Fe(III) oxyhydroxide colloids in freshwater and brackish seawater, with incorporation of phosphate and calcium. Geochimica et Cosmochimica Acta 66:745-758.

Heiri, O., Lotter, A.F., Lemcke, G. 2001. Loss on ignition as a method for estimating organic and carbonate content in sediments: reproducibility and comparability of results. Journal of Paleolimnology 25:101-110.

Jones, M.N. 1984. Nitrate reduction by shaking with cadmium: alternative to cadmium columns. Water Research 18:643-646.

Kudo, I., Hisatoku, T., Yoshimura, T., Maita, Y. 2015. Primary productivity and nitrogen assimilation with identifying the contribution of urea in Funka Bay, Japan. Earth, Coastal and Shelf Science 158:12-19.

Lapointe, B.E., Herren, L.W., Debortoli, D.D., Vogel, M.A., 2015. Evidence of sewage-driven eutrophication and harmful algal blooms in Florida’s Indian River Lagoon. Harmful Algae 43:82-102.

Long, E.R., Macdonald, D.D., Smith, S.L., Calder, F.D. 1995. Incidence of adverse biological effects with ranges of chemical concentrations in marine and estuarine sediments. Environmental Management 19:81-97.

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Millero, F.J. 2006. Chemical Oceanography. Taylor & Francis Group, Boca Raton, FL, 496 pp.

National Research Council. 1997. Contaminated sediments in ports and waterways: Cleanup strategies and technologies. Committee on Contaminated Marine Sediments, Marine Board, Commission on Engineering and Technical Systems, National Research Council. National Academy Press, Washington, DC, 284 pp.

Redfield, A.C. 1934. On the proportions of organic derivatives in sea water and their relation to the composition of plankton. In James Johnstone Memorial Volume (Daniel, R.J., editor), pp. 176-192. University of Liverpool.

Trefry, J.H., Stauble, D.K., Sisler, M.A., Tiernan, D., Trocine, R.P., Metz, S., Glascock, C.J., Bader, S.F. 1987. Origin, composition and fate of organic-rich sediments in coastal estuaries. Final Report to The Florida Sea Grant College and the Florida Department of Environmental Regulation, (Project R/IRL-2), 103 pp.

Trefry, J.H., Metz, S., Trocine, R.P., Iricanin, N., Burnside, D., Chen, N., Webb, B. 1990. Design and operation of a muck sediment survey. Special Report to the St. Johns River Water Management District. Palatka, Fl. SJ90-SP3, 62 pp.

Trefry J.H., Trocine R.P. 1991. Collection and analysis of marine particles for trace elements. Pp. 311–315 in: Hurd DC, Spencer DW, ed. Marine Particles: Analysis and Characterization. Geophysical Monograph 63, American Geophysical Union, Washington, DC.

Trefry, J.H., Trocine, R.P., Roy, S. 2002. Pre-Dredging and post-Dredging surveys of trace metals and organic substances in Turkey Creek, Florida. Final Report to BCI Engineers and Scientists, Inc. and St. Johns River Water Management District, 31pp.

Trefry, J.H., Trocine, R.P., Rember, R.D., Little, C.R. 2004. Post-dredge evaluation of Crane Creek: Sediment trapping efficiency and sediment quality. Final Report to St. Johns River Water Management District.

Trefry, J.H., Trocine, R.P., Woodall, D.W. 2007. Composition and sources of suspended matter in the Indian River Lagoon, Florida. Florida Scientist 70:363382.

Trefry, J.H., Windsor, Jr., J.G., Trocine, R.P. 2008. Toxic substances in the Indian River lagoon. Final Report to St. Johns River Water Management District, Contract SJ47613.

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Trefry, J.H., Trocine, R.P. 2011. Metals in sediments and clams from the Indian River Lagoon, Florida: 2006-7 versus 1992. Florida Scientist 74:43-62.

Trefry, J.H., Pandit, A., Martin, J.B. 2014. Sediment survey and fluxes of nutrients from sediments and groundwater in the northern Indian River Lagoon, Florida. Annual Report for Contract #27815, St. Johns River Water Management District, Palatka, FL.

Trefry, J.H., Pandit, A., Martin, J.B. 2015. Sediment survey and fluxes of nutrients from sediments and groundwater in the northern Indian River Lagoon, Florida. End of Fiscal Year Report for Contract #27815, November 2015, St. Johns River Water Management District, Palatka, FL.

Trocine, R. P., Trefry, J.H. 1996. Metal concentrations in sediment, water and clams from the Indian River Lagoon, Florida. Marine Pollution Bulletin 32:754–759.

U.S. Environmental Protection Agency. 1991. Methods for the Determination of Metals in Environmental Samples. Office of Research & Development, U.S. EPA, Cincinnati, Ohio.

Van Mooy, B.A.S., Krupke, A., Dyhrman, S.T., Fredricks, H.F., Frischkorn, K.R., Ossolinski, J.E., Repeta, D.J., Rouco, M., Seewald, J.D., Sylva, S.P. 2015. Major role of planktonic phosphate reduction in the marine phosphorus redox cycle. Science 348:783-785.

Wedepohl KH. 1995. The composition of the continental crust. Geochimica et Cosmochimica Acta 59:1217-1232.

Windsor, J.G., Jr., Surma, J.M. 1993. Toxic substances survey for the Indian River Lagoon system: Organic chemicals. Final Report to St. Johns River Water Management District. 173 pp.

Windsor, J.G., Jr. 2004. A comparison of polycyclic aromatic hydrocarbons and phthalate esters levels in Crane Creek Florida Sediment for 1992 and 2003. Final Report to St. Johns River Water Management District.

Zimmerman, A.E., Allison, S.D., Martiny, A.C. 2014. Phylogenetic constraints on elemental stoichiometry and resource allocation in heterotrophic marine bacteria. Environmental Microbiology 16:1398-1410.

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3.7 Appendices Appendix A. Sampling grid and data from muck survey. Grids are identified by letter and number. Dimensions (N-S, 1 sec of latitude, 30.5 m) (E-W, 1 sec of longitude, 27.5 m).

A F K P U AA

601

610

620

630

640

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Appendix A (continued) Data from muck survey.

Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) L610 28.0392 80.5803 1.0 1.00 0.00 Sand L611 28.0389 80.5803 1.3 1.30 0.00 Sand L612 28.0386 80.5803 1.3 1.46 0.16 Light muck L613 28.0384 80.5803 1.3 1.38 0.08 Hard to light muck L614 28.0381 80.5803 1.2 1.24 0.04 Wet Sand L615 28.0378 80.5803 1.2 1.25 0.05 Sandy L616 28.0375 80.5803 1.6 1.65 0.10 L617 28.0373 80.5803 2.1 2.45 0.35 Soupy muck L618 28.0370 80.5803 2.7 3.30 0.60 Soupy muck L619 28.0367 80.5803 2.5 5.00 2.50 Fine soup on top L620 28.0364 80.5803 2.5 5.40 2.90 Very soft, hard sand bottom L621 28.0361 80.5803 2.6 5.30 2.75 Not hard bottom at 5.3m L622 28.0359 80.5803 3.0 5.40 2.40 Sand at bottom L623 28.0356 80.5802 3.0 5.40 2.40 Hard at 5.4m L624 28.0353 80.5803 2.7 3.00 0.30 Shell hash, 30cm of hash L625 28.0351 80.5803 2.6 3.05 0.45 Sand at 3.05m L626 28.0348 80.5802 2.5 2.50 0.00 At marking 10 (holding on), shell L627 28.0345 80.5802 0.9 0.88 0.00 Sand 15 ft from shore K626 28.0347 80.5806 1.5 1.50 0.00 Sand 20ft from shore K625 28.0350 80.5806 2.3 2.50 0.20 Hard at 2.5m K624 28.0353 80.5806 2.8 3.00 0.20 Hard at 3m, sand and shell K623 28.0356 80.5806 3.0 3.60 0.60 K622 28.0358 80.5805 3.1 4.55 1.45 K621 28.0361 80.5806 3.0 5.50 2.50 hard at 5.5m K620 28.0364 80.5806 2.7 5.50 2.80 dense muck at mid muck K619 28.0367 80.5806 2.7 3.50 0.80 muck over shell hash K618 28.0370 80.5806 2.5 3.50 1.00 Sand at 3.5 K617 28.0372 80.5806 2.1 2.40 0.35 Hard shell at 2.4 K616 28.0375 80.5805 1.4 1.70 0.30 Light muck but gritty K615 28.0378 80.5805 1.2 1.55 0.32 Low water content - gritty muck K614 28.0380 80.5805 1.2 1.40 0.20 Hard to no penetration/ patchy thickness K613 28.0383 80.5805 1.3 1.62 0.37

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Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) K611 28.0389 80.5805 1.2 1.25 0.05 K610 28.0392 80.5806 1.1 1.10 0.00 Hard sand 30 feet from shore J625 28.0349 80.5808 0.9 0.90 0.00 sand 10 feet from shoe J624 28.0353 80.5808 2.5 2.50 0.00 Hard sand 30 feet from shore J623 28.0356 80.5808 2.9 3.20 0.30 Hard at 3.2, soft at muck top J622 28.0358 80.5809 3.8 5.10 1.35 At piling #2, really soft on really hard J621 28.0361 80.5808 3.1 3.80 0.70 Soft over hard J620 28.0364 80.5809 3.0 3.50 0.50 Soft over hard J619 28.0367 80.5808 2.9 3.90 1.00 Soft over hard, feels very fine J618 28.0369 80.5808 2.6 5.15 2.55 Not as hard at 5.15 J617 28.0372 80.5808 1.8 2.40 0.65 Shelly at 2.4, jack hammer to 3.0 J616 28.0375 80.5808 1.4 1.63 0.25 Soft, hard at 1.63 J615 28.0378 80.5808 1.1 1.70 0.60 Stiff muck/grainy. Hard at 1.7 J614 28.0381 80.5808 1.1 1.72 0.62 Hard at 1.72 J613 28.0383 80.5808 1.3 1.53 0.28 Hard at 1.53 J612 28.0386 80.5808 1.2 1.25 0.10 Wet sand not muck J611 28.0389 80.5808 1.1 1.10 0.00 J610 28.0392 80.5809 0.8 0.80 0.00 40 feet from shore M627 28.0345 80.5800 1.6 1.65 0.05 Soft sand/shell at top, 25 feet from shore M626 28.0348 80.5800 3.0 3.60 0.60 In channel, high density at 3.6. Stiff, but not hard at 3.6 M625 28.0350 80.5800 2.5 3.40 0.90 Stiffer muck, not completely hard bottom M624 28.0353 80.5800 2.6 3.17 0.62 Stiffer muck, not completely hard bottom. Stiff at 3.17 M623 28.0355 80.5800 2.7 5.30 2.60 Hard at 5.3 M622 28.0358 80.5800 2.7 5.30 2.65 Hard at 5.3 M621 28.0361 80.5800 2.3 5.25 3.00 Hard at 5.25 M620 28.0364 80.5800 2.3 4.70 2.40 Shelly at 4.7, a bit loose M619 28.0367 80.5800 2.3 5.25 2.95 M618 28.0370 80.5800 2.4 5.45 3.10 Chunky big stuff, wiggles around

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Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) M616 28.0375 80.5800 1.1 1.10 0.00 Hard M615 28.0378 80.5800 1.1 1.05 0.00 Hard M614 28.0381 80.5801 1.1 1.15 0.05 Wet sand M613 28.0384 80.5800 1.35 1.40 0.05 Wet sand M612 28.0386 80.5800 1.50 1.65 0.15 Wet sand with minor muck M611 28.0389 80.5800 1.50 1.60 0.10 Wet sand with minor muck M610 28.0392 80.5800 1.35 1.45 0.10 Wet sand with minor muck I623 28.0356 80.5811 1.20 1.20 0.00 Wet sand with minor muck, 30 feet from shore I622 28.0358 80.5812 1.60 1.80 0.20 Sandy muck, hard bottom, patchy I621 28.0362 80.5811 3.40 4.70 1.30 Soft/hard at bottom I620 28.0365 80.5811 3.00 4.70 1.70 Soft/hard at bottom, hammer to 5.2 hard I618 28.0369 80.5811 2.80 3.80 1.00 Hard at 3.8 I617 28.0372 80.5810 1.70 2.70 1.00 Hard at 2.0 I616 28.0375 80.5809 1.30 1.80 0.50 Grainy/stiff muck I615 28.0378 80.5811 1.00 1.50 0.50 Hard surface layer I614 28.0381 80.5811 1.10 1.60 0.50 Hard bottom - sand I613 28.0384 80.5810 1.15 1.50 0.35 Hard bottom - sand I612 28.0387 80.5811 1.10 1.50 0.40 Wet sand I611 28.0389 80.5809 1.05 1.10 0.05 Wet sand, shell hash I610 28.0392 80.5812 0.70 0.70 0.00 H611 28.0389 80.5814 0.95 1.00 0.05 H612 28.0386 80.5813 1.10 1.20 0.10 H613 28.0383 80.5815 1.10 1.45 0.35 Hard bottom H614 28.0380 80.5813 1.10 1.70 0.60 H615 28.0377 80.5813 1.00 1.80 0.80 Hard bottom H616 28.0374 80.5814 0.95 0.95 0.00 H597 28.0428 80.5813 1.26 1.26 0.00 Hard K601 28.0416 80.5806 0.85 0.85 0.00 Hard, very dark shallow water P601 28.0417 80.5792 1.55 1.55 0.00 Hard U601 28.0417 80.5778 1.74 1.74 0.00 Hard sand 30 feet from shore Z601 28.0417 80.5763 2.15 2.15 0.00 Hard AE606 28.0403 80.5750 2.20 2.20 0.00 Hard

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Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) U606 28.0403 80.5778 1.86 1.86 0.00 Hard P606 28.0403 80.5792 1.70 1.75 0.05 Sandy, very loose muck P606A 28.0402 80.5797 1.10 1.10 0.00 Hard P610 28.0392 80.5792 1.60 1.72 0.12 Sandy Muck P611 28.0389 80.5792 1.56 1.74 0.18 U611 28.0389 80.5778 1.95 1.95 0.00 In channel, hard Z611 28.0389 80.5764 2.20 2.20 0.00 Hard AE611 28.0389 80.5750 2.25 2.25 0.00 Hard AE616 28.0375 80.5750 2.34 2.34 0.00 Hard, deep water Z616 28.0375 80.5764 2.18 2.18 0.00 Hard U616 28.0375 80.5778 1.74 1.74 0.00 Hard Z621 28.0362 80.5764 2.25 2.28 0.03 Loose wet sand layer Z626 28.0347 80.5764 1.65 1.65 0.00 Hard AE621 28.0362 80.5750 2.3 2.32 0.02 Fine wet sandy layer on top R613 28.0385 80.5786 1.75 1.80 0.05 Between Markers 1-2 in channel P613 28.0383 80.5790 1.56 1.70 0.14 Stiff clay, in channel O615A 28.0378 80.5794 1.64 1.76 0.12 Between Markers 3-4 in channel O616A 28.0376 80.5796 1.52 1.65 0.13 Between markers 5-6 in channel, really loose top N617A 28.0372 80.5798 1.55 1.62 0.07 Between Markers 7-8 in channel, very flocky top N617 28.0372 80.5797 1.6 1.66 0.06 N618 28.0370 80.5797 2.4 3.80 1.40 N619 28.0367 80.5797 2.4 5.20 2.80 N620 28.0364 80.5797 2.2 4.90 2.70 N621 28.0361 80.5797 2.4 5.10 2.70 N622 28.0358 80.5797 2.35 5.00 2.65 Unsure of water depth N623 28.0356 80.5797 2.4 4.45 2.05 N624 28.0353 80.5797 2.25 2.80 0.55 Muck and sand, 10m offshore N625 28.0350 80.5797 1.3 1.55 0.25 Gravel and muck N626 28.0347 80.5798 1.65 1.72 0.07 Sandy (wet) N627 28.0344 80.5797 1.68 1.68 0.00 Hard O627 28.0345 80.5794 2.65 3.05 0.40 Sandy O624 28.0354 80.5796 0.78 0.78 0.00 Hard, 5m offshore

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Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) O621 28.0361 80.5795 0.45 0.45 0.00 Rock/oyster reef O621A 28.0361 80.5795 2.05 2.15 0.10 Shells O620 28.0364 80.5795 0.57 0.57 0.10 Rock/oyster reef O619 28.0367 80.5795 0.68 0.68 0.00 Rock/oyster reef O618 28.0370 80.5795 0.66 0.66 0.00 Hard (reef), 10m offshore O617 28.0372 80.5795 1.45 2.00 0.55 O617A 28.0373 80.5793 0.65 0.65 0.00 Rock/oyster reef, 10m offshore O616 28.0375 80.5795 1.65 2.05 0.40 Hard bottom (rock) O615 28.0378 80.5795 1.6 1.72 0.12 Mucky, hit hard bottom O614 28.0381 80.5795 1.26 1.36 0.10 Hit hard bottom O613 28.0384 80.5794 1.28 1.35 0.07 N612 28.0386 80.5797 1.25 1.40 0.15 N613 28.0384 80.5797 1.06 1.11 0.05 N614 28.0381 80.5797 0.98 1.04 0.06 Sandy (wet) N615 28.0378 80.5797 0.9 0.90 0.00 Hard N616 28.0375 80.5797 1.06 1.06 0.00 Sand P616 28.0375 80.5793 0.58 0.58 0.00 Near Marker 5: hard, sandy P615 28.0377 80.5792 0.95 0.95 0.00 Hard Q615 28.0378 80.5789 0.88 0.88 0.00 Hard I612 28.0386 80.5811 0.92 1.00 0.08 Sandy wet I611 28.0389 80.5811 0.82 0.82 0.00 Hard H611 28.0389 80.5814 0.58 0.58 0.00 Hard H612 28.0386 80.5814 0.9 1.02 0.12 Wet sand H613 28.0383 80.5815 0.9 1.20 0.30 H614 28.0380 80.5815 0.9 1.30 0.40 Very variable, definitely muck H615 28.0378 80.5814 0.84 1.52 0.68 H616 28.0375 80.5814 0.76 0.82 0.06 H617 28.0372 80.5814 0.84 1.15 0.31 H618 28.0370 80.5814 1.80 2.70 0.90 H619 28.0367 80.5814 2.00 4.40 2.40 H620 28.0364 80.5814 2.30 5.30 3.00 Hard sandy bottom H621 28.0364 80.5814 1.02 1.02 0.00 Sand H622 28.0359 80.5814 0.80 1.15 0.35 G621 28.0361 80.5817 0.56 1.28 0.72 Muck, 5m offshore G620 28.0364 80.5817 0.90 1.16 0.26

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Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) G618 28.0370 80.5817 1.06 1.62 0.56 G617 28.0372 80.5817 0.90 1.60 0.70 G616 28.0375 80.5817 0.94 1.58 0.64 Pockets of muck G615 28.0378 80.5817 0.95 0.95 0.00 Hard, pockets of much G614 28.0381 80.5817 0.90 1.42 0.52 Pockets of muck G613 28.0383 80.5817 0.90 1.25 0.35 Pockets of muck G612 28.0386 80.5816 0.78 0.94 0.16 G611 28.0388 80.5817 0.44 0.44 0.00 Hard F612 28.0386 80.5819 0.47 0.47 0.00 Hard, pockets of muck F613 28.0383 80.5820 0.78 1.28 0.50 F614 28.0381 80.5820 0.85 1.42 0.57 F615 28.0378 80.5820 0.88 1.45 0.57 F616 28.0375 80.5820 0.62 0.62 0.00 Hard F617 28.0387 80.5820 0.48 0.48 0.00 Hard F618 28.0370 80.5818 0.38 0.38 0.00 F616A 28.0374 80.5821 0.38 0.38 0.00 Hard F615A 28.0378 80.5821 0.40 0.40 0.00 Hard E614 28.0381 80.5821 0.40 0.40 0.00 Hard I619 28.0367 80.5811 2.40 4.90 2.50 O628 28.0342 80.5795 2.90 3.00 0.10 Sandy O629 28.0339 80.5794 3.00 3.00 0.00 Hard N631 28.0334 80.5797 2.44 2.44 0.00 Rock, under bridge O630A 28.0335 80.5795 3.05 3.05 0.00 Between Markers 13-14, hard O630 28.0336 80.5794 3.95 3.95 0.00 Hard N628 28.0343 80.5797 0.54 0.54 0.00 Hard P628 28.0342 80.5792 2.10 2.25 0.15 Sandy muck P629 28.0339 80.5791 1.50 3.00 1.50 P630 28.0336 80.5792 1.30 1.75 0.45 Sandy muck O629A 28.0340 80.5795 1.25 1.25 0.00 Hard O629B 28.0338 80.5795 1.10 1.10 0.00 Hard N631A 28.0334 80.5797 4.00 4.20 0.20 Under east side of bridge, 20cm muck N631B 28.0334 80.5798 3.10 3.45 0.35 Under west side of bridge L632 28.0331 80.5803 2.92 2.92 0.00 Hard K632 28.0331 80.5805 2.56 2.56 0.00 Hard J631 28.0333 80.5808 3.00 3.00 0.00 Hard

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Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) I629 28.0339 80.5812 3.20 4.00 0.80 Very loose J632 28.0331 80.5808 2.70 2.70 0.00 Hard I631 28.0334 80.5813 2.90 2.90 0.00 Hard H632 28.0331 80.5814 3.00 4.60 1.60 H633 28.0328 80.5814 3.50 3.50 0.00 Hard H634 28.0326 80.5815 4.00 4.50 0.50 H635 28.0322 80.5814 3.30 4.10 0.80 H636 28.0319 80.5814 3.90 4.50 0.60 H637 28.0316 80.5813 1.40 2.70 1.30 H637A 28.0316 80.5813 0.70 0.70 0.00 Hard I637 28.0317 80.5811 3.50 4.70 1.20 I636 28.0320 80.5811 3.60 4.75 1.15 I635 28.0322 80.5811 3.45 4.36 0.91 I634 28.0325 80.5811 4.40 4.60 0.20 Sandy I633 28.0328 80.5811 3.38 3.38 0.00 Hard I632 28.0331 80.5812 2.80 4.40 1.60 K633 28.0328 80.5806 3.00 3.40 0.40 Very loose, fine, flocky K634 28.0325 80.5806 3.00 3.03 0.03 Hard K635 28.0323 80.5806 2.70 4.38 1.68 J633 28.0329 80.5809 3.10 3.57 0.47 Mushy bottom J634 28.0325 80.5808 3.00 3.05 0.05 Super soft top - flock. Super hard bottom J635 28.0323 80.5808 2.55 4.25 1.70 J636 28.0320 80.5809 3.00 4.95 1.95 J637 28.0317 80.5809 3.45 3.45 0.00 Hard J637A 28.0316 80.5808 1.10 2.20 1.10 J638 28.0315 80.5808 0.55 2.20 1.65 Stiff sandy wet with brown muck (not gray muck) G637 28.0317 80.5815 1.10 2.10 1.00 Shelly at 1.1, hard bottom G637A 28.0317 80.5816 0.65 0.75 0.10 Shell hash G636 28.0319 80.5817 2.70 4.05 1.35 G635 28.0324 80.5817 2.95 3.35 0.40 Mushy G633A 28.0327 80.5816 3.05 4.45 1.40 G633 28.0328 80.5817 2.30 2.85 0.55 Shelly G633B 28.0329 80.5818 2.80 4.45 1.65 G631 28.0334 80.5817 1.80 2.60 0.80 G631A 28.0334 80.5818 0.60 1.00 0.40

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Station Latitude Longitude Water Total Muck Comment (˚N) (˚W) Depth Depth Depth (m) (m) (m) F636 28.0320 80.5820 1.70 2.90 1.20 Shell hash, stiff clay F636A 28.0319 80.5820 0.70 0.70 0.00 Hard E636 28.0319 80.5822 1.60 1.60 0.00 Hard: shell and gravel E636A 28.0320 80.5823 2.00 2.80 0.80 Under middle trestle, stiff clay F634 28.0325 80.5820 1.05 1.05 0.00 Sand/shell F632 28.0330 80.5819 1.30 2.40 1.10 Really soft top E631 28.0332 80.5821 0.90 2.00 1.10 Really soft L637 28.0316 80.5802 1.60 3.25 1.65 M638 28.0313 80.5801 1.70 3.00 1.30 M639 28.0311 80.5800 1.50 2.25 0.75 M640 28.0308 80.5800 1.30 2.03 0.73 Clay layer at 1.9 M639A 28.0311 80.5800 0.25 0.25 0.00 East side of canal, hard M634 28.0324 80.5799 1.20 2.10 0.90 L634 28.0325 80.5803 1.92 1.92 0.00 Hard M633 28.0327 80.5800 1.05 1.05 0.00 Hard H634 28.0326 80.5813 3.95 4.55 0.60 N631C 28.0334 80.5797 3.55 4.15 0.60 Loose under US1

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Appendix B. Selected Quality Assurance and Quality Control Data

Quality Assurance and Quality Control Data for Sediment Metal Analyses.

Results for the Standard Reference Material (SRM) #2704 Buffalo River Sediment certified

by the National Institute of Standards and Technology (NIST), Certified Reference Material

(CRM) MESS-3 Marine Sediment certified by the National Research Council of Canada

(NRC), and LECO Calibration Material 502-509 (Lot 1012).

Reference Material Al Fe Si TOC LOI CaCO3 N P (%) (%) (%) (%) (%) (%) (%) (µg/g)

SRM #2704 6.14 4.17 29.13 - - - - 983 This Study 6.04 4.17 28.96 - - - - 1011

SRM #2704 6.11 4.11 29.08 3.348 - - - 998 NIST Certified Values ± 0.16 ± 0.10 ± 0.13 ± 0.016 - - - ± 28

CRM MESS-3 - - - 2.03 - - 0.17 - This Study - - - 2.04 - - 0.14 - - - - 2.03 - - 0.14 - - - - 2.01 - - 0.16 -

CRM MESS-3 8.59 4.34 27* 2** - - - 0.12* NRC Certified Values ± 0.23 ± 0.11 ------

LECO 502-309 - - - 11.66 - - 0.91 - This Study - - - 11.68 - - 0.90 - - - - 11.75 - - 0.90 -

LECO 502-309 - - - 11.98** - - 0.93 - LECO Calibration Values - - - ± 0.44 - - ± 0.04 -

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* Information Value. **Total carbon (organic plus inorganic).

Sediment Metal Analysis (continued)

Method Detection Limits (MDLs).

Al Fe Si TOC LOI CaCO3 N P (%) (%) (%) (%) (%) (%) (%) (µg/g) Method Detection Limit 0.01 0.01 0.03 0.03 0.1 0.2 0.02 0.9

Percent Spike Recovery.

Al Fe Si TOC LOI CaCO3 N P K622 94.9 95.1 102.8 - - - - 108.4

Estimate of Precision as Percent Relative Standard Deviation (RSD) of Lab Duplicates.

Al Fe Si TOC LOI CaCO3 N P K615 3.4 1.9 0.4 1.6 2.0 0 0 2.3

TCK (18-20 cm) 0.4

TC3 (8-10 cm) 2.0 0 5.8 0

Percent RSD = (standard deviation / mean) X 100.

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QA/QC Data for Dissolved Nutrients

Method Detection Limit (MDLs). Nitrate‐ Total Total Ammonium Nitrite Nitrogen Phosphate Phosphorus (µM) (µM) (µM) (µM) (µM) Method Detection Limit 0.3 0.2 0.03* 0.04 0.03* * MDL for SEAL AA3 Autoanalyzer

Estimate of Precision as the average ± SD of the Relative Standard Deviation (RSD) of Lab Duplicates. The number of duplicates is indicated in parenthesis Nitrate‐ Total Total Ammonium Nitrite Nitrogen Phosphate Phosphorus

Average ± SD of (10) 2.4 ± (10) 6.1 ± (10) 2.1 ± (10) 0.6 ± RSD 3.8 4.8 1.8 1.2 (11) 2.6 ± 2.4

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Quality Assurance and Quality Control Data for Suspended Solids' Metals, Carbon and Nitrogen Analyses.

Results for the Standard Reference Material (SRM) #2704 Buffalo River Sediment certified by the National Institute of Standards and Technology (NIST) and Leco Calibration Material 502-309 (Lot 1012).

Standard Reference Al Fe Si P POC N Material (%) (%) (%) (µg/g)(%) (%)

SRM #2704 5.96 4.14 29.11 990 - - This Study 6.26 4.11 29.12 1025 - - 6.14 4.13 29.09 973 - - 6.19 4.16 29.39 1010 - - 6.16 4.11 29.04 1020 - - 6.10 4.19 29.11 1001 - - 6.15 4.12 29.01 1007 - - 6.05 4.10 29.04 984 - - 6.10 4.13 29.00 989 - - 6.01 4.11 29.00 1010 - - 5.99 4.04 29.15 975 - - 6.11 4.17 29.08 1023 - - 6.13 4.19 29.05 976 - - 6.08 4.13 28.89 1002 - - 6.22 4.20 29.11 992 - - 5.97 4.02 29.09 1014 - - 6.22 4.20 29.12 1015 6.23 4.18 29.17 1006

SRM #2704 6.11 4.11 29.08 998 - - ± ± ± NIST Certified Values 0.16 0.10 0.13 ± 28 - -

LECO 502-309 - - - - 11.7 0.90 This Study - - - - 11.7 0.90 - - - - 11.7 0.89 - - - - 11.7 0.90 - - - - 11.7 0.92 11.7 0.91 11.8 0.94

LECO 502-309 - - - - 11.98* 0.93 LECO Calibration Values - - - - ±0.44 ± 0.04

* Total carbon (organic and inorganic).

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Brevard County: Turkey Creek 2015

Quality Assurance and Quality Control Data for Suspended Solids' Metals, Carbon and Nitrogen Analyses.

Method Detection Limits (MDLs).

Al Fe Si P POC N (%) (%) (%) (%) (%) (%)

Particulate Method Detection Limit* 0.03 0.03 0.43 0.001 0.1 0.5

DOC (µg/L) (µg/L) (µg/L) (µg/L) (mg/L) (µg/L) Dissolved Method Detection Limit - - - - 0.2 -

* Based on 1 mg of suspended matter.

Percent Spike Recovery.

Al Fe Si P

Particulate Metals 95.6 93.3 100.3 103.7 Mean 94.5 96.7 99.4 105.1 Standard Deviation 97.7 91.8 101.8 92.0 (n = ) 94.7 96.2 93.9 93.3 102.4 96.4 94.8 102.2 92.9 93.5 99.7 93.9 99.3 94.5 101.8 97.2 99.0 97.6 96.1 94.7 99.0 103.3 94.8 105.8 102.0 97.3 96.7 94.2 92.7 93.8 100.3 101.1 99.7 94.3 96.0 94.7 97.8 103.8 95.6 108.1 101.5 93.9 98.2 92.2 97.4 97.0 101.3 95.5 97.0 93.5 97.2 93.4 103.9 93.8 95.4 104.7 98.2 94.9 98.1 92.0

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Brevard County: Turkey Creek 2015

Quality Assurance and Quality Control Data for Suspended Solids' Metals, Carbon and Nitrogen Analyses.

Estimate of Precision as Percent Relative Standard Deviation (RSD) of Lab and Field Duplicates.

Al Fe Si P POC N DOC

TC4 (0.5 m) 5-4-15 0.3 4.6 0.5 6.6 2.4 4.2 1.1 TC4 (0.5 m) 6-16-15 ------0 TC2 (0.5 m) 7-16-15 1.7 2.8 1.6 1.1 0.2 1.3 1.7 TC1 (0.5 m) 9-9-15 3.1 4.2 3.1 6.8 3.4 8.0 4.5 TC1 (0.5 m) 10-14-15 0 8.5 3.4 4.4 1.0 0 1.3 TC3 (0.5 m) 12-14-15 4.7 2.9 2.3 0 0 2.3 0

Percent RSD = (standard deviation / mean) X 100.

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Appendix C1. Concentrations of dissolved and particulate parameters for Stations 1-5 for April 22, 2015.

Brevard County: Turkey Creek, April 22, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Water Ammonium Nitrate + ΣN Phosphat ΣP DOC Alkalinity (mg- Temp.* DO* DO* Station Location Salinity* pH* Depth (m) (µM) Nitrite (µM) (µM) e (µM) (µM) (mM) CaCO3/L) (°C) (%) (mg/L) TC1 28° 02.419'N 0.5 4.9 0.81 38.8 0.57 1.13 0.92 117 23.6 27.7 72.9 5.03 7.24 80° 34.574'W 1.0 6.2 0.49 40.4 0.78 1.45 0.99 123 24.1 27.9 71.3 4.89 7.28 1.75 7.1 0.59 36.7 0.92 1.51 1.03 119 24.7 28.1 68.0 4.63 7.36 TC2 28° 02.334'N 0.5 5.2 0.51 37.8 0.63 1.34 0.95 120 23.9 28.1 71.3 4.88 7.31 80° 34.748'W 1.0 5.6 0.49 37.4 0.70 1.31 0.86 122 24.1 28.1 67.6 4.62 7.33 1.3 5.7 0.50 36.7 0.73 1.32 0.69 125 24.2 28.1 66.7 4.56 7.35 TC3 28° 02.267'N 0.5 4.6 0.43 44.1 0.62 1.77 1.05 137 23.6 28.2 71.8 4.92 7.36 80° 34.828'W 0.9 4.5 0.40 36.3 0.52 1.25 0.90 133 23.8 28.2 69.3 4.74 7.37 TC4 28° 02.147'N 0.5 3.6 0.30 40.4 0.57 1.59 0.96 131 23.5 28.8 79.7 5.40 7.50 80° 34.853'W 1.0 4.0 0.32 21.4 0.62 1.48 0.87 133 23.7 28.5 74.0 5.04 7.44 2.0 5.6 0.83 54.2 1.29 3.48 1.02 134 24.8 28.8 42.0 2.82 7.27 3.25 2.8 0.39 32.5 1.91 2.36 0.86 137 25.2 28.9 5.3 0.36 7.01 TC5 28° 01.953'N 0.5 5.3 1.63 36.8 1.06 1.63 1.27 164 7.3 27.7 75.0 5.67 7.06 80° 34.852'W 1.0 6.1 0.57 40.5 1.11 2.02 0.95 133 23.6 28.6 65.5 4.45 7.19 2.5 12.8 0.52 45.7 5.50 5.68 0.84 143 25.2 29.1 8.4 0.56 7.05 *Sonde

Brevard County: Turkey Creek, April 22, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

Alkalinity Water Ammonium Nitrate + Nitrite ΣN (µg- Phosphat ΣP (µg- DOC Temp.* DO* DO* Station Location (mg Salinity* pH* Depth (m) (µg-N/L) (µg-N/L) N/L) e (µg-P/L) P/L) (mg/L) (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.419'N 0.5 68.6 11.3 543 17.7 35.1 11.0 117 23.6 27.7 72.9 5.03 7.24 80° 34.574'W 1.0 86.9 6.9 567 24.1 45.0 11.9 123 24.1 27.9 71.3 4.89 7.28 1.75 99.5 8.2 514 28.5 46.8 12.4 119 24.7 28.1 68.0 4.63 7.36 TC2 28° 02.334'N 0.5 72.9 7.2 530 19.6 41.4 11.4 120 23.9 28.1 71.3 4.88 7.31 80° 34.748'W 1.0 78.5 6.8 524 21.8 40.7 10.3 122 24.1 28.1 67.6 4.62 7.33 1.3 79.9 7.0 514 22.6 40.8 8.3 125 24.2 28.1 66.7 4.56 7.35 TC3 28° 02.267'N 0.5 64.4 6.1 618 19.4 55.0 12.6 137 23.6 28.2 71.8 4.92 7.36 80° 34.828'W 0.9 63.0 5.5 509 16.1 38.6 10.8 133 23.8 28.2 69.3 4.74 7.37 TC4 28° 02.147'N 0.5 50.4 4.2 565 17.7 49.4 11.5 131 23.5 28.8 79.7 5.40 7.50 80° 34.853'W 1.0 56.0 4.5 300 19.4 45.7 10.4 133 23.7 28.5 74.0 5.04 7.44 2.0 78.5 11.6 759 39.9 107.9 12.2 134 24.8 28.8 42.0 2.82 7.27 3.25 39.2 5.5 455 59.2 73.2 10.3 137 25.2 28.9 5.3 0.36 7.01 TC5 28° 01.953'N 0.5 74.3 22.9 515 32.8 50.4 15.3 164 7.3 27.7 75.0 5.67 7.06 80° 34.852'W 1.0 85.5 7.9 568 34.5 62.5 11.4 133 23.6 28.6 65.5 4.45 7.19 2.5 179 7.3 640 170.3 176.1 10.1 143 25.2 29.1 8.4 0.56 7.05 *Sonde

3‐62 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C1 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for April 22, 2015.

Brevard County: Turkey Creek, April 22, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (%) (µM) TC1 28° 02.419'N 0.5 3.2 1.9 25.0 2.09 2.27 12.8 0.4 0.41 19.5 0.052 3.4 7.7 80° 34.574'W 1.0 3.9 1.8 25.0 1.87 1.93 11.8 0.5 0.57 18.0 0.059 2.6 7.3 1.75 3.9 2.2 26.0 1.29 2.27 14.4 0.3 0.37 16.5 0.054 2.7 7.6 TC2 28° 02.334'N 0.5 3.0 1.4 26.0 2.21 2.28 13.5 0.4 0.39 20.2 0.050 4.0 8.5 80° 34.748'W 1.0 4.2 2.2 26.0 1.76 2.12 13.6 0.4 0.52 14.9 0.052 3.0 8.9 1.3 4.1 2.2 26.0 1.61 2.29 14.1 0.4 0.49 14.3 0.049 2.2 6.5 TC3 28° 02.267'N 0.5 4.9 2.3 24.0 1.50 2.04 9.8 0.6 0.88 17.8 0.073 4.8 16.9 80° 34.828'W 0.9 8.4 4.1 25.0 3.20 2.79 16.0 0.3 0.78 11.7 0.082 1.8 10.8 TC4 28° 02.147'N 0.5 5.9 3.5 25.0 1.40 1.90 9.6 0.7 1.27 18.4 0.090 5.6 23.4 80° 34.853'W 1.0 4.7 3.1 26.0 2.02 2.38 11.8 0.6 0.83 25.3 0.098 5.2 17.3 2.0 29.1 4.5 26.0 0.18 0.19 1.0 0.7 6.29 44.4 1.074 10.8 224 3.3 2.6 1.6 28.0 1.57 2.32 9.1 0.8 0.63 34.5 0.074 7.4 13.7 TC5 28° 01.953'N 0.5 4.0 3.1 5.0 2.39 5.42 11.5 0.7 0.87 22.5 0.076 3.8 11.0 80° 34.852'W 1.0 3.5 2.7 25.0 1.60 2.72 9.6 0.6 0.71 27.2 0.079 5.5 13.7 2.5 4.2 2.4 28.0 1.21 3.69 9.0 0.8 1.04 23.9 0.084 4.5 13.6 *Refractometer

Brevard County: Turkey Creek, April 22, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

PO Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON Station Location Salinity* N Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (µg/L) (%) TC1 28° 02.419'N 0.5 3.2 1.9 25.0 2.09 2.27 12.8 0.4 12.7 19.5 0.6 3.4 108 80° 34.574'W 1.0 3.9 1.8 25.0 1.87 1.93 11.8 0.5 17.7 18.0 0.7 2.6 102 1.75 3.9 2.2 26.0 1.29 2.27 14.4 0.3 11.4 16.5 0.6 2.7 106 TC2 28° 02.334'N 0.5 3.0 1.4 26.0 2.21 2.28 13.5 0.4 12.2 20.2 0.6 4.0 119 80° 34.748'W 1.0 4.2 2.2 26.0 1.76 2.12 13.6 0.4 16.2 14.9 0.6 3.0 125 1.3 4.1 2.2 26.0 1.61 2.29 14.1 0.4 15.3 14.3 0.6 2.2 90.7 TC3 28° 02.267'N 0.5 4.9 2.3 24.0 1.50 2.04 9.8 0.6 27.1 17.8 0.9 4.8 237 80° 34.828'W 0.9 8.4 4.1 25.0 3.20 2.79 16.0 0.3 24.3 11.7 1.0 1.8 151 TC4 28° 02.147'N 0.5 5.9 3.5 25.0 1.40 1.90 9.6 0.7 39.3 18.4 1.1 5.6 328 80° 34.853'W 1.0 4.7 3.1 26.0 2.02 2.38 11.8 0.6 25.7 25.3 1.2 5.2 243 2.0 29.1 4.5 26.0 0.18 0.19 1.0 0.7 194.7 44.4 12.9 10.8 3138 3.25 2.6 1.6 28.0 1.57 2.32 9.1 0.8 19.4 34.5 0.9 7.4 192 TC5 28° 01.953'N 0.5 4.0 3.1 5.0 2.39 5.42 11.5 0.7 27.1 22.5 0.9 3.8 154 80° 34.852'W 1.0 3.5 2.7 25.0 1.60 2.72 9.6 0.6 22.1 27.2 1.0 5.5 193 2.5 4.2 2.4 28.0 1.21 3.69 9.0 0.8 32.1 23.9 1.0 4.5 190 * Refractometer

3‐63 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C2. Concentrations of dissolved and particulate parameters for Stations 1-5 for May 4, 2015.

Brevard County: Turkey Creek, May 04, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammonium Nitrate + ΣN Phosphat ΣP DOC Temp.* DO* DO* Station Location (mg- Salinity* pH* Depth (m) (µM) Nitrite (µM) (µM) e (µM) (µM) (mM) (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.421'N 0.5 6.9 0.35 33.7 0.23 0.87 0.85 128 25.8 24.2 96.2 6.96 8.24 80° 34.638'W 1.0 7.0 0.36 34.4 0.25 0.86 0.85 130 25.8 24.2 97.3 7.04 8.21 1.75 6.9 0.22 33.4 0.24 0.94 0.82 130 25.8 24.2 96.9 7.01 8.19 TC2 28° 02.336'N 0.5 6.7 0.33 34.4 0.20 0.87 0.87 136 20.5 24.8 82.3 6.08 8.00 80° 34.762'W 1.0 5.5 0.18 35.2 0.19 0.74 0.87 129 25.3 24.1 88.1 6.40 8.19 1.3 6.9 0.46 33.8 0.19 0.65 0.80 141 25.4 24.2 86.8 6.30 8.18 TC3 28° 02.273'N 0.5 3.3 0.62 35.4 0.54 1.31 1.06 168 16.4 24.4 78.3 5.96 7.89 80° 34.830'W 0.9 6.9 0.46 34.6 0.19 0.85 0.84 132 24.3 24.9 67.5 4.86 8.00 TC4 28° 02.145'N 0.5 3.2 0.67 35.3 0.59 1.26 1.08 176 15.9 25.2 83.8 6.30 7.82 80° 34.853'W 1.0 7.6 0.36 38.1 0.34 1.35 1.01 133 24.4 26.2 79.4 5.60 7.98 2.0 10.0 0.42 40.2 0.49 1.35 0.92 127 25.1 25.9 73.2 5.17 7.99 3.0 11.5 0.27 43.0 0.77 1.58 0.95 133 25.2 25.8 66.0 4.66 7.97 TC5 28° 01.944'N 0.5 3.8 0.48 37.8 0.85 1.66 1.13 175 17.8 26.2 77.6 5.67 7.81 80° 34.876'W 1.0 9.0 0.30 41.3 1.35 2.31 1.01 133 23.6 26.6 62.1 4.37 7.90 2.5 12.4 0.25 46.6 2.39 2.98 0.93 131 25.2 26.4 53.3 3.73 7.88 *Sonde

Brevard County: Turkey Creek, May 04, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

Nitrate + ΣN Alkalinity Water Ammonium Phosphate ΣP (µg- DOC Temp.* DO* DO* Station Location Nitrite (µg- (µg- (mg Salinity* pH* Depth (m) (µg-N/L) (µg-P/L) P/L) (mg/L) (°C) (%) (mg/L) N/L) N/L) CaCO3/L) TC1 28° 02.421'N 0.5 96.7 5.0 472 7.2 27.1 10.2 128 25.8 24.2 96.2 6.96 8.24 80° 34.638'W 1.0 98.1 5.1 482 7.9 26.6 10.2 130 25.8 24.2 97.3 7.04 8.21 1.75 96.7 3.1 468 7.6 29.0 9.8 130 25.8 24.2 96.9 7.01 8.19 TC2 28° 02.336'N 0.5 93.9 4.6 482 6.3 26.9 10.4 136 20.5 24.8 82.3 6.08 8.00 80° 34.762'W 1.0 77.1 2.6 493 6.0 23.0 10.4 129 25.3 24.1 88.1 6.40 8.19 1.3 96.7 6.4 474 6.0 20.0 9.6 141 25.4 24.2 86.8 6.30 8.18 TC3 28° 02.273'N 0.5 46.2 8.8 496 16.8 40.6 12.7 168 16.4 24.4 78.3 5.96 7.89 80° 34.830'W 0.9 96.7 6.4 484 6.0 26.4 10.1 132 24.3 24.9 67.5 4.86 8.00 TC4 28° 02.145'N 0.5 44.1 9.3 495 18.4 39.0 13.0 176 15.9 25.2 83.8 6.30 7.82 80° 34.853'W 1.0 106 5.1 533 10.4 42.0 12.1 133 24.4 26.2 79.4 5.60 7.98 2.0 140 5.8 563 15.2 41.7 11.0 127 25.1 25.9 73.2 5.17 7.99 3.0 161 3.7 602 23.9 49.0 11.4 133 25.2 25.8 66.0 4.66 7.97 TC5 28° 01.944'N 0.5 53.2 6.7 530 26.4 51.5 13.6 175 17.8 26.2 77.6 5.67 7.81 80° 34.876'W 1.0 126 4.2 578 41.9 71.5 12.1 133 23.6 26.6 62.1 4.37 7.90 2.5 174 3.4 653 74.0 92.2 11.2 131 25.2 26.4 53.3 3.73 7.88 *Sonde

3‐64 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C2 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for May 4, 2015.

Brevard County: Turkey Creek, May 04, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (%) (µM) TC1 28° 02.421'N 0.5 4.3 2.3 25.0 2.52 2.32 17.8 0.3 0.45 13.5 0.049 2.7 8.4 80° 34.638'W 1.0 4.5 2.5 24.0 2.22 2.42 17.9 0.3 0.45 13.7 0.052 2.7 8.7 1.75 4.7 2.5 24.0 2.14 2.38 17.9 0.3 0.47 14.0 0.055 3.9 13.2 TC2 28° 02.336'N 0.5 14.1 8.8 24.0 2.20 3.07 19.1 0.3 1.14 10.3 0.121 1.5 15.1 80° 34.762'W 1.0 14.0 9.1 24.0 3.15 3.50 19.1 0.2 1.04 14.3 0.166 2.1 20.9 1.3 30.2 20.1 24.0 2.84 3.27 18.8 0.2 1.85 13.8 0.347 3.9 84.1 TC3 28° 02.273'N 0.5 6.3 3.2 11.0 2.51 3.07 13.8 0.4 0.79 11.3 0.059 1.9 8.5 80° 34.830'W 0.9 53.4 24.2 24.0 2.81 3.32 19.9 0.2 3.28 9.6 0.427 1.8 68.6 TC4 28° 02.145'N 0.5 4.7 3.4 12.0 2.46 4.31 15.4 0.5 0.82 17.7 0.070 3.4 11.5 80° 34.853'W 1.0 7.9 3.7 22.0 2.46 2.95 14.7 0.5 1.35 16.1 0.105 3.2 18.0 2.0 5.0 3.1 24.0 2.04 2.66 15.1 0.5 0.80 19.2 0.081 4.4 15.8 3.0 6.2 3.6 24.0 1.83 2.83 14.9 0.5 1.03 16.9 0.087 3.4 14.9 TC5 28° 01.944'N 0.5 4.0 3.2 12.0 2.06 3.88 11.5 0.8 0.97 25.6 0.084 5.0 14.1 80° 34.876'W 1.0 4.3 2.5 22.0 1.68 2.60 13.9 0.7 0.95 24.3 0.087 5.0 15.4 2.5 5.6 4.2 25.0 2.16 3.32 15.6 0.6 1.04 18.3 0.085 3.6 14.3 *Refractometer

Brevard County: Turkey Creek, May 04, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) (µg/L)

TC1 28° 02.421'N 0.5 4.3 2.3 25.0 2.52 2.32 17.8 0.3 13.9 13.5 0.6 2.7 117 80° 34.638'W 1.00 4.5 2.5 24.0 2.22 2.42 17.9 0.3 14.0 13.7 0.6 2.7 122 1.8 4.7 2.5 24.0 2.14 2.38 17.9 0.3 14.7 14.0 0.7 3.9 185 TC2 28° 02.336'N 0.5 14.1 8.8 24.0 2.20 3.07 19.1 0.3 35.3 10.3 1.5 1.5 212 80° 34.762'W 1.0 14.0 9.1 24.0 3.15 3.50 19.1 0.2 32.1 14.3 2.0 2.1 293 1.3 30.2 20.1 24.0 2.84 3.27 18.8 0.2 57.4 13.8 4.2 3.9 1180 TC3 28° 02.273'N 0.5 6.3 3.2 11.0 2.51 3.07 13.8 0.4 24.5 11.3 0.7 1.9 119 80° 34.830'W 0.9 53.4 24.2 24.0 2.81 3.32 19.9 0.2 101.4 9.6 5.1 1.8 961 TC4 28° 02.145'N 0.5 4.7 3.4 12.0 2.46 4.31 15.4 0.5 25.4 17.7 0.8 3.4 161 80° 34.853'W 1.0 7.9 3.7 22.0 2.46 2.95 14.7 0.5 41.7 16.1 1.3 3.2 252 2.0 5.0 3.1 24.0 2.04 2.66 15.1 0.5 24.7 19.2 1.0 4.4 222 3.0 6.2 3.6 24.0 1.83 2.83 14.9 0.5 32.0 16.9 1.0 3.4 209 TC5 28° 01.944'N 0.5 4.0 3.2 12.0 2.06 3.88 11.5 0.8 30.0 25.6 1.0 5.0 198 80° 34.876'W 1.0 4.3 2.5 22.0 1.68 2.60 13.9 0.7 29.3 24.3 1.0 5.0 216 2.5 5.6 4.2 25.0 2.16 3.32 15.6 0.6 32.3 18.3 1.0 3.6 201 * Refractometer

3‐65 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C3. Concentrations of dissolved and particulate parameters for Stations 1-5 for June 16, 2015.

Brevard County: Turkey Creek, June 16, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammonium Nitrate + ΣN Phosphat ΣP DOC Temp.* DO* DO* Station Location (mg- Salinity* pH* Depth (m) (µM) Nitrite (µM) (µM) e (µM) (µM) (mM) (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.416'N 0.5 2.6 0.24 38.7 0.14 0.57 0.81 122 22.4 29.6 89.2 6.00 8.01 80° 34.577'W 1.0 2.5 0.37 38.1 0.20 0.64 0.85 123 23.1 30.2 99.9 6.62 8.01 1.5 2.5 0.25 37.9 0.15 0.54 0.79 127 23.5 30.2 99.4 6.58 8.00 1.75 2.7 0.32 36.9 0.20 0.62 0.72 128 24.0 30.4 92.0 6.06 7.97 TC2 28° 02.332'N 0.5 2.3 0.37 37.7 0.14 0.58 0.97 128 22.2 29.9 90.6 6.08 7.95 80° 34.749'W 1.25 2.5 0.28 36.9 0.16 0.58 0.92 125 23.5 30.5 87.1 5.74 7.94 TC3 28° 02.266'N 0.5 ------21.7 30.4 98.8 6.58 7.96 80° 34.831'W 0.9 ------22.9 30.7 95.7 6.31 7.96 TC4 28° 02.148'N 0.5 2.4 0.32 37.9 0.21 0.66 0.74 127 23.4 30.4 90.1 5.95 8.00 80° 34.852'W 1.0 2.6 0.33 38.4 0.18 0.75 1.05 125 23.5 30.7 88.1 5.79 7.99 2.0 2.9 0.31 39.1 0.42 1.09 0.68 131 25.0 31.5 60.0 3.85 7.99 2.5 4.3 0.27 48.7 0.98 2.66 0.87 134 25.1 31.3 41.8 2.69 7.85 3.0 3.6 0.32 43.3 1.12 1.91 0.72 135 25.1 31.0 18.9 1.22 7.70 TC5 28° 01.954'N 0.5 4.2 0.67 45.3 0.71 1.41 1.02 168 4.3 30.2 81.7 6.02 7.70 80° 34.850'W 1.0 3.0 0.34 38.7 0.46 1.40 0.85 125 12.6 30.8 82.9 5.77 7.58 2.0 3.4 0.32 40.7 1.30 2.58 0.78 130 23.7 30.5 54.6 3.59 7.76 2.5 5.2 0.29 52.7 1.61 3.90 1.08 135 23.7 30.4 42.5 2.81 7.64 *Sonde

Brevard County: Turkey Creek, June 16, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

ΣP Alkalinity Water Ammonium Nitrate + ΣN (µg-Phosphate DOC Temp.* DO* DO* Station Location (µg- (mg Salinity* pH* Depth (m) (µg-N/L) Nitrite (µg-N/L) N/L) (µg-P/L) (mg/L) (°C) (%) (mg/L) P/L) CaCO3/L) TC1 28° 02.416'N 0.5 36.4 3.3 542 4.4 17.6 9.7 122 22.4 29.6 89.2 6.00 8.01 80° 34.577'W 1.0 35.0 5.1 533 6.3 19.7 10.2 123 23.1 30.2 99.9 6.62 8.01 1.5 35.0 3.5 531 4.7 16.9 9.5 127 23.5 30.2 99.4 6.58 8.00 1.75 37.8 4.4 517 6.3 19.2 8.6 128 24.0 30.4 92.0 6.06 7.97 TC2 28° 02.332'N 0.5 32.2 5.1 528 4.4 18.0 11.7 128 22.2 29.9 90.6 6.08 7.95 80° 34.749'W 1.25 35.0 3.9 516 5.0 18.0 11.1 125 23.5 30.5 87.1 5.74 7.94 TC3 28° 02.266'N 0.5 ------21.7 30.4 98.8 6.58 7.96 80° 34.831'W 0.9 ------22.9 30.7 95.7 6.31 7.96 TC4 28° 02.148'N 0.5 33.6 4.5 531 6.4 20.5 8.9 127 23.4 30.4 90.1 5.95 8.00 80° 34.852'W 1.0 36.4 4.6 538 5.4 23.1 12.6 125 23.5 30.7 88.1 5.79 7.99 2.0 40.6 4.4 547 13.1 33.7 8.2 131 25.0 31.5 60.0 3.85 7.99 2.5 60.2 3.8 683 30.5 82.3 10.4 134 25.1 31.3 41.8 2.69 7.85 3.0 50.4 4.5 607 34.8 59.2 8.7 135 25.1 31.0 18.9 1.22 7.70 TC5 28° 01.954'N 0.5 58.8 9.4 635 22.0 43.8 12.3 168 4.3 30.2 81.7 6.02 7.70 80° 34.850'W 1.0 42.0 4.7 542 14.4 43.4 10.2 125 12.6 30.8 82.9 5.77 7.58 2.0 47.6 4.5 570 40.2 80.0 9.4 130 23.7 30.5 54.6 3.59 7.76 2.5 72.9 4.1 738 49.8 120.9 13.0 135 23.7 30.4 42.5 2.81 7.64 *Sonde

3‐66 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C3 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for June 16, 2015. Brevard County: Turkey Creek, June 16, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

PO Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON Station Location Salinity* N Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (µM) (%) TC1 28° 02.416'N 0.5 2.2 1.1 24.0 1.43 1.87 16.8 0.5 0.32 19.6 0.036 4.0 6.4 80° 34.577'W 1.0 2.4 0.9 24.5 2.64 2.24 18.1 0.4 0.31 20.7 0.041 3.9 6.7 1.5 4.3 2.0 25.0 3.43 2.91 22.3 0.3 0.35 15.5 0.056 2.6 8.0 1.75 8.9 4.4 26.0 3.33 3.40 20.1 0.2 0.69 11.4 0.084 3.3 21.0 TC2 28° 02.332'N 0.5 2.2 1.0 25.0 2.80 1.82 15.0 0.5 0.32 24.7 0.046 4.2 6.6 80° 34.749'W 1.25 3.7 2.0 25.5 2.46 1.91 15.0 0.5 0.56 24.4 0.074 4.1 10.7 TC3 28° 02.266'N 0.5 ------80° 34.831'W 0.9 ------TC4 28° 02.148'N 0.5 3.3 1.6 24.0 2.67 2.11 13.7 0.6 0.60 22.2 0.060 6.4 14.9 80° 34.852'W 1.0 5.1 2.7 26.0 1.88 1.55 11.0 0.6 0.95 26.7 0.114 3.8 13.9 2.0 6.7 3.2 27.0 2.13 1.84 11.1 0.7 1.44 25.2 0.140 6.0 28.5 2.5 8.0 2.8 27.5 1.21 1.23 6.7 1.0 2.54 22.5 0.149 4.3 24.4 3.0 4.9 1.5 27.5 1.36 1.74 9.8 1.0 1.57 19.5 0.079 3.8 13.2 TC5 28° 01.954'N 0.5 8.5 4.6 10.0 1.28 2.45 7.4 1.2 3.25 22.9 0.163 3.8 23.1 80° 34.850'W 1.0 5.3 2.7 26.0 2.05 2.33 11.4 0.7 1.20 17.7 0.078 3.0 11.4 2.0 4.0 2.5 26.5 1.62 2.65 10.9 0.8 1.06 19.7 0.065 4.5 12.7 2.5 6.6 3.6 26.5 0.66 1.39 5.1 1.1 2.22 22.8 0.125 3.2 15.0 *Refractometer

Brevard County: Turkey Creek, June 16, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) (µg/L)

TC1 28° 02.416'N 0.5 2.2 1.1 24.0 1.43 1.87 16.8 0.5 10.1 19.6 0.4 4.0 89.4 80° 34.577'W 1.0 2.4 0.9 24.5 2.64 2.24 18.1 0.4 9.6 20.7 0.5 3.9 93.2 1.5 4.3 2.0 25.0 3.43 2.91 22.3 0.3 10.8 15.5 0.7 2.6 112 1.75 8.9 4.4 26.0 3.33 3.40 20.1 0.2 21.4 11.4 1.0 3.3 294 TC2 28° 02.332'N 0.5 2.2 1.0 25.0 2.80 1.82 15.0 0.5 10.0 24.7 0.5 4.2 93.1 80° 34.749'W 1.25 3.7 2.0 25.5 2.46 1.91 15.0 0.5 17.2 24.4 0.9 4.1 150 TC3 28° 02.266'N 0.5 ------80° 34.831'W 0.9 ------TC4 28° 02.148'N 0.5 3.3 1.6 24.0 2.67 2.11 13.7 0.6 18.6 22.2 0.7 6.4 208 80° 34.852'W 1.0 5.1 2.7 26.0 1.88 1.55 11.0 0.6 29.3 26.7 1.4 3.8 195 2.0 6.7 3.2 27.0 2.13 1.84 11.1 0.7 44.6 25.2 1.7 6.0 399 2.5 8.0 2.8 27.5 1.21 1.23 6.7 1.0 78.7 22.5 1.8 4.3 342 3.0 4.9 1.5 27.5 1.36 1.74 9.8 1.0 48.7 19.5 0.9 3.8 185 TC5 28° 01.954'N 0.5 8.5 4.6 10.0 1.28 2.45 7.4 1.2 100.7 22.9 2.0 3.8 324 80° 34.850'W 1.0 5.3 2.7 26.0 2.05 2.33 11.4 0.7 37.2 17.7 0.9 3.0 159 2.0 4.0 2.5 26.5 1.62 2.65 10.9 0.8 32.9 19.7 0.8 4.5 179 2.5 6.6 3.6 26.5 0.66 1.39 5.1 1.1 68.9 22.8 1.5 3.2 210 * Refractometer

3‐67 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C4. Concentrations of dissolved and particulate parameters for Stations 1-5 for July 16, 2015.

Brevard County: Turkey Creek, July 16, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammonium Nitrate + ΣN Phosphate ΣP DOC Salinity Temp.* DO* DO* Station Location (mg- pH* Depth (m) (µM) Nitrite (µM) (µM) (µM) (µM) (mM) * (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.420'N 0.5 2.2 0.33 41.9 0.49 1.36 1.39 121 26.7 29.0 52.0 3.46 7.99 80° 34.586'W 1.0 3.7 0.37 40.8 0.52 1.36 1.05 131 28.2 29.7 54.8 3.57 7.99 1.5 3.7 0.42 40.3 0.52 1.44 1.09 140 28.3 29.7 44.7 2.91 7.99 1.75 3.9 0.38 48.8 0.56 1.46 1.20 132 28.3 29.7 44.1 2.87 7.99 TC2 28° 02.333'N 0.5 3.7 0.29 41.9 0.51 1.45 1.03 131 27.1 29.1 47.2 3.12 7.96 80° 34.753'W 1.25 3.8 0.29 50.7 0.57 1.61 1.15 133 28.2 29.8 38.5 2.50 7.96 TC3 28° 02.269'N 0.5 ------26.0 29.6 40.9 2.69 7.89 80° 34.830'W 0.9 ------27.7 29.8 36.8 2.40 7.93 TC4 28° 02.146'N 0.5 4.9 0.28 67.2 1.17 2.64 1.11 126 - - - - - 80° 34.850'W 1.0 3.8 0.36 56.5 0.76 2.15 1.03 128 Sonde malfunctioned in field 2.0 4.1 0.30 55.4 0.69 1.71 1.05 134 - - - - - 2.5 4.2 0.40 64.1 0.67 1.70 1.04 132 - - - - - 3.0 4.4 0.30 59.3 0.78 1.89 0.97 141 - - - - - TC5 28° 01.949'N 0.5 8.2 0.80 71.7 1.66 2.95 1.32 156 - - - - - 80° 34.853'W 1.0 6.3 0.38 66.7 1.06 2.30 1.00 137 - - - - - 2.0 4.2 0.36 56.0 0.79 1.69 0.98 135 - - - - - 2.5 5.0 0.26 64.4 0.78 1.90 1.00 136 - - - - - *Sonde

Brevard County: Turkey Creek, July 16, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

Nitrate + ΣP Alkalinity Water Ammonium ΣN (µg- Phosphat DOC Salinity Temp.* DO* DO* Station Location Nitrite (µg- (µg- (mg pH* Depth (m) (µg-N/L) N/L) e (µg-P/L) (mg/L) * (°C) (%) (mg/L) N/L) P/L) CaCO3/L) TC1 28° 02.420'N 0.5 30.8 4.6 587 15.3 42.1 16.7 121 26.7 29.0 52.0 3.46 7.99 80° 34.586'W 1.0 51.8 5.1 572 16.2 42.1 12.6 131 28.2 29.7 54.8 3.57 7.99 1.5 51.8 5.9 565 16.2 44.5 13.1 140 28.3 29.7 44.7 2.91 7.99 1.75 54.6 5.3 684 17.2 45.3 14.4 132 28.3 29.7 44.1 2.87 7.99 TC2 28° 02.333'N 0.5 51.8 4.1 587 15.8 45.1 12.4 131 27.1 29.1 47.2 3.12 7.96 80° 34.753'W 1.25 53.2 4.1 710 17.5 49.8 13.8 133 28.2 29.8 38.5 2.50 7.96 TC3 28° 02.269'N 0.5 ------26.0 29.6 40.9 2.69 7.89 80° 34.830'W 0.9 ------27.7 29.8 36.8 2.40 7.93 TC4 28° 02.146'N 0.5 68.6 3.9 942 36.2 81.7 13.3 126 - - - - - 80° 34.850'W 1.0 53.2 5.1 792 23.6 66.7 12.4 128 Sonde malfunctioned in field 2.0 57.4 4.3 776 21.4 53.1 12.6 134 - - - - - 2.5 58.8 5.6 898 20.7 52.7 12.5 132 - - - - - 3.0 61.6 4.2 831 24.3 58.5 11.7 141 - - - - - TC5 28° 01.949'N 0.5 115 11.2 1010 51.6 91.4 15.9 156 - - - - - 80° 34.853'W 1.0 88.3 5.3 934 32.9 71.3 12.0 137 - - - - - 2.0 58.8 5.0 785 24.5 52.5 11.8 135 - - - - - 2.5 70.1 3.7 902 24.2 58.8 12.0 136 - - - - - *Sonde

3‐68 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C4 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for July 16, 2015.

Brevard County: Turkey Creek, July 16, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (%) (µM) TC1 28° 02.420'N 0.5 5.6 4.0 28.0 1.97 1.61 7.6 0.6 1.07 29.3 0.137 4.6 18.5 80° 34.586'W 1.0 7.1 4.2 30.0 2.22 1.74 10.3 0.5 1.23 24.9 0.147 4.4 22.2 1.5 7.8 5.1 31.0 1.96 1.85 10.9 0.5 1.20 23.0 0.149 3.9 21.6 1.75 8.2 5.5 31.0 1.93 1.77 10.1 0.5 1.27 22.6 0.155 3.9 22.9 TC2 28° 02.333'N 0.5 6.8 4.9 29.0 1.67 1.53 7.8 0.6 1.41 30.4 0.172 5.3 25.4 80° 34.753'W 1.25 7.6 4.8 30.0 1.87 1.76 10.0 0.6 1.42 25.7 0.162 4.3 23.2 TC3 28° 02.269'N ------80° 34.830'W ------TC4 28° 02.146'N 0.5 9.8 3.4 29.5 0.84 0.87 3.8 0.9 2.94 26.4 0.215 6.2 43.3 80° 34.850'W 1.0 8.9 3.6 30.0 0.82 0.93 4.4 0.9 2.45 32.2 0.239 6.2 39.4 2.0 9.5 4.3 30.0 1.07 1.09 5.4 0.7 2.18 27.0 0.214 4.9 33.2 2.5 9.8 4.0 30.0 1.01 1.19 6.2 0.7 2.32 27.4 0.224 5.0 35.1 3.0 8.3 3.7 30.0 1.47 1.27 7.6 0.7 1.75 27.7 0.192 5.0 29.7 TC5 28° 01.949'N 0.5 6.5 2.8 15.5 1.76 2.75 7.3 0.9 1.82 28.9 0.158 5.3 24.8 80° 34.853'W 1.0 7.5 3.1 29.0 0.74 1.01 4.0 0.9 2.05 33.7 0.209 8.1 43.1 2.0 6.8 3.5 30.0 1.16 1.06 5.4 0.7 1.53 32.3 0.182 5.8 28.0 2.5 8.1 3.8 30.0 1.28 1.34 5.8 0.8 2.01 27.6 0.186 5.2 30.0 *Refractometer

Brevard County: Turkey Creek, July 16, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) (µg/L)

TC1 28° 02.420'N 0.5 5.6 4.0 28.0 1.97 1.61 7.6 0.6 33.2 29.3 1.6 4.6 259 80° 34.586'W 1.0 7.1 4.2 30.0 2.22 1.74 10.3 0.5 38.2 24.9 1.8 4.4 311 1.5 7.8 5.1 31.0 1.96 1.85 10.9 0.5 37.2 23.0 1.8 3.9 302 1.75 8.2 5.5 31.0 1.93 1.77 10.1 0.5 39.4 22.6 1.9 3.9 320 TC2 28° 02.333'N 0.5 6.8 4.9 29.0 1.67 1.53 7.8 0.6 43.8 30.4 2.1 5.3 356 80° 34.753'W 1.25 7.6 4.8 30.0 1.87 1.76 10.0 0.6 43.8 25.7 1.9 4.3 325 TC3 28° 02.269'N ------80° 34.830'W ------TC4 28° 02.146'N 0.5 9.8 3.4 29.5 0.84 0.87 3.8 0.9 91.0 26.4 2.6 6.2 607 80° 34.850'W 1.0 8.9 3.6 30.0 0.82 0.93 4.4 0.9 75.8 32.2 2.9 6.2 553 2.0 9.5 4.3 30.0 1.07 1.09 5.4 0.7 67.5 27.0 2.6 4.9 466 2.5 9.8 4.0 30.0 1.01 1.19 6.2 0.7 71.8 27.4 2.7 5.0 492 3.0 8.3 3.7 30.0 1.47 1.27 7.6 0.7 54.1 27.7 2.3 5.0 417 TC5 28° 01.949'N 0.5 6.5 2.8 15.5 1.76 2.75 7.3 0.9 56.3 28.9 1.9 5.3 347 80° 34.853'W 1.0 7.5 3.1 29.0 0.74 1.01 4.0 0.9 63.3 33.7 2.5 8.1 604 2.0 6.8 3.5 30.0 1.16 1.06 5.4 0.7 47.4 32.3 2.2 5.8 393 2.5 8.1 3.8 30.0 1.28 1.34 5.8 0.8 62.3 27.6 2.2 5.2 421 * Refractometer

3‐69 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C5. Concentrations of dissolved and particulate parameters for Stations 1-5 for August 26, 2015.

Brevard County: Turkey Creek, August 26, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammonium Nitrate + ΣN Phosphate ΣP DOC Temp.* DO* DO* Station Location (mg- Salinity* pH* Depth (m) (µM) Nitrite (µM) (µM) (µM) (µM) (mM) (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.416'N 0.5 3.0 0.32 46.4 0.40 1.20 0.86 121 19.4 31.8 55.4 3.65 8.01 80° 34.576'W 1.75 3.2 0.36 49.6 0.35 1.14 0.79 111 19.9 32.0 55.9 3.67 8.10 TC2 28° 02.334'N 0.5 3.2 0.40 49.3 0.54 1.25 0.74 123 19.4 32.1 44.8 2.94 7.93 80° 34.752'W 1.25 3.2 0.50 47.9 0.65 1.44 0.76 120 19.7 32.1 31.7 2.08 7.95 TC3 28° 02.268'N 0.5 3.7 0.49 53.6 0.64 1.53 0.82 122 18.4 32.4 40.8 2.68 7.87 80° 34.832'W ------TC4 28° 02.147'N 0.5 4.0 0.52 58.3 0.82 1.80 0.79 116 18.9 32.7 43.3 2.83 7.75 80° 34.852'W 1.0 3.7 0.47 57.2 1.08 1.99 1.16 120 19.4 32.4 19.4 1.27 7.79 2.0 3.7 0.38 55.7 0.90 1.85 0.80 125 19.5 32.2 10.8 0.70 7.81 2.5 3.3 0.43 57.8 0.82 1.81 0.77 127 19.6 32.2 8.8 0.58 7.83 3.0 62.5 0.13 168 8.78 8.59 0.82 137 19.6 31.4 4.6 0.30 7.24 TC5 28° 01.952'N 0.5 3.8 2.66 64.2 1.16 1.55 1.10 169 4.9 31.3 73.9 5.32 7.49 80° 34.849'W 1.0 7.1 0.40 66.8 1.68 2.44 0.78 117 19.0 32.6 28.2 1.84 7.64 1.5 14.4 0.32 76.3 4.49 4.78 0.76 122 19.1 32.1 16.3 1.07 7.65 2.0 41.0 0.22 109 8.71 8.77 0.80 132 19.1 31.5 5.0 0.33 7.45 2.5 49.9 0.24 125 9.97 9.79 0.80 137 19.0 31.2 3.4 0.23 7.39 *Sonde

Brevard County: Turkey Creek, August 26, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

ΣN ΣP Alkalinity Water Ammonium Nitrate + Nitrite Phosphate DOC Temp.* DO* DO* Station Location (µg- (µg- (mg Salinity* pH* Depth (m) (µg-N/L) (µg-N/L) (µg-P/L) (mg/L) (°C) (%) (mg/L) N/L) P/L) CaCO3/L) TC1 28° 02.416'N 0.5 41.6 4.5 650 12.5 37.0 10.3 121 19.4 31.8 55.4 3.65 8.01 80° 34.576'W 1.75 45.4 5.0 695 10.9 35.4 9.5 111 19.9 32.0 55.9 3.67 8.10 TC2 28° 02.334'N 0.5 44.8 5.5 690 16.6 38.9 8.9 123 19.4 32.1 44.8 2.94 7.93 80° 34.752'W 1.25 44.3 7.0 671 20.2 44.5 9.1 120 19.7 32.1 31.7 2.08 7.95 TC3 28° 02.268'N 0.5 52.4 6.8 751 19.9 47.5 9.8 122 18.4 32.4 40.8 2.68 7.87 80° 34.832'W ------TC4 28° 02.147'N 0.5 56.6 7.3 816 25.3 55.8 9.5 116 18.9 32.7 43.3 2.83 7.75 80° 34.852'W 1.0 51.1 6.5 801 33.4 61.7 13.9 120 19.4 32.4 19.4 1.27 7.79 2.0 51.1 5.3 780 27.9 57.2 9.6 125 19.5 32.2 10.8 0.70 7.81 2.5 45.7 6.1 809 25.3 56.0 9.2 127 19.6 32.2 8.8 0.58 7.83 3.0 876 1.8 2350 271.8 266.2 9.9 137 19.6 31.4 4.6 0.30 7.24 TC5 28° 01.952'N 0.5 52.8 37.3 900 36.0 48.0 13.2 169 4.9 31.3 73.9 5.32 7.49 80° 34.849'W 1.0 98.8 5.6 936 52.1 75.6 9.4 117 19.0 32.6 28.2 1.84 7.64 1.5 202 4.4 1070 139.1 148.1 9.1 122 19.1 32.1 16.3 1.07 7.65 2.0 575 3.1 1530 269.8 271.6 9.6 132 19.1 31.5 5.0 0.33 7.45 2.5 699 3.4 1750 308.8 303.1 9.6 137 19.0 31.2 3.4 0.23 7.39 *Sonde

3‐70 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C5 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for August 26, 2015.

Brevard County: Turkey Creek, August 26, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (%) (µM) TC1 28° 02.416'N 0.5 5.5 4.8 20.0 0.73 0.93 10.3 0.7 1.19 26.4 0.121 5.0 19.6 80° 34.576'W 1.75 13.0 7.9 20.0 1.85 1.71 14.5 0.5 2.02 13.0 0.141 3.1 28.8 TC2 28° 02.334'N 0.5 7.5 6.2 20.0 1.02 1.01 7.6 0.7 1.73 29.8 0.187 6.4 34.4 80° 34.752'W 1.25 9.1 7.3 20.0 1.01 1.04 8.8 0.7 1.96 29.8 0.225 5.3 34.3 TC3 28° 02.268'N 0.5 9.1 6.1 20.0 0.77 1.00 4.7 0.8 2.36 33.4 0.254 5.9 38.4 80° 34.832'W ------TC4 28° 02.147'N 0.5 11.0 8.8 20.0 0.73 0.83 4.3 0.9 3.35 35.4 0.325 6.5 51.2 80° 34.852'W 1.0 10.1 8.8 20.0 0.54 0.89 4.7 0.9 2.82 30.5 0.257 6.2 44.9 2.0 9.6 8.2 20.0 0.60 0.59 4.7 0.8 2.55 32.7 0.262 6.4 43.9 2.5 9.2 7.6 20.0 0.65 0.77 6.5 0.9 2.51 30.2 0.230 6.1 39.9 3.0 6.8 10.7 20.0 0.78 0.56 4.6 0.8 1.76 36.6 0.208 5.9 28.7 TC5 28° 01.952'N 0.5 3.4 2.9 3.0 2.15 4.56 7.8 0.9 0.93 25.4 0.072 6.5 15.8 80° 34.849'W 1.0 10.4 6.7 20.0 0.79 0.43 2.5 0.9 2.84 33.8 0.291 4.9 36.2 1.5 7.3 8.5 20.0 0.67 0.74 2.6 0.9 2.23 31.9 0.195 6.9 36.1 2.0 6.5 11.4 20.0 0.82 0.52 2.8 1.0 2.03 36.7 0.198 5.8 26.8 2.5 5.6 15.7 20.0 0.67 0.47 2.6 1.0 1.80 38.4 0.178 6.2 24.6 *Refractometer

Brevard County: Turkey Creek, August 26, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

PO PON Water TSS Turbidity Al Fe Si ΣP ΣP POC POC Station Location Salinity* N (µg/L Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) ) TC1 28° 02.416'N 0.5 5.5 4.8 20.0 0.73 0.93 10.3 0.7 36.9 26.4 1.5 5.0 275 80° 34.576'W 1.75 13.0 7.9 20.0 1.85 1.71 14.5 0.5 62.4 13.0 1.7 3.1 403 TC2 28° 02.334'N 0.5 7.5 6.2 20.0 1.02 1.01 7.6 0.7 53.4 29.8 2.2 6.4 482 80° 34.752'W 1.25 9.1 7.3 20.0 1.01 1.04 8.8 0.7 60.8 29.8 2.7 5.3 481 TC3 28° 02.268'N 0.5 9.1 6.1 20.0 0.77 1.00 4.7 0.8 72.9 33.4 3.0 5.9 538 80° 34.832'W ------TC4 28° 02.147'N 0.5 11.0 8.8 20.0 0.73 0.83 4.3 0.9 103.7 35.4 3.9 6.5 717 80° 34.852'W 1.0 10.1 8.8 20.0 0.54 0.89 4.7 0.9 87.2 30.5 3.1 6.2 629 2.0 9.6 8.2 20.0 0.60 0.59 4.7 0.8 78.8 32.7 3.1 6.4 615 2.5 9.2 7.6 20.0 0.65 0.77 6.5 0.9 77.9 30.2 2.8 6.1 559 3.0 6.8 10.7 20.0 0.78 0.56 4.6 0.8 54.5 36.6 2.5 5.9 402 TC5 28° 01.952'N 0.5 3.4 2.9 3.0 2.15 4.56 7.8 0.9 28.9 25.4 0.9 6.5 221 80° 34.849'W 1.0 10.4 6.7 20.0 0.79 0.43 2.5 0.9 88.0 33.8 3.5 4.9 507 1.5 7.3 8.5 20.0 0.67 0.74 2.6 0.9 69.0 31.9 2.3 6.9 506 2.0 6.5 11.4 20.0 0.82 0.52 2.8 1.0 62.8 36.7 2.4 5.8 375 2.5 5.6 15.7 20.0 0.67 0.47 2.6 1.0 55.6 38.4 2.1 6.2 345 * Refractometer

3‐71 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C6. Concentrations of dissolved and particulate parameters for Stations 1-5 for September 9, 2015.

Brevard County: Turkey Creek, September 09, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammoniu Nitrate + ΣN Phosphate ΣP DOC Temp.* DO* DO* Station Location (mg- Salinity* pH* Depth (m) m (µM) Nitrite (µM) (µM) (µM) (µM) (mM) (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.421'N 0.5 2.6 0.41 42.6 0.45 1.08 0.91 150 16.6 29.6 76.8 5.34 7.92 80° 34.575'W 1.75 3.4 0.35 46.5 0.76 1.37 0.70 139 17.6 30.0 59.8 4.10 7.88 TC2 28° 02.337'N 0.5 3.5 1.28 51.0 0.91 1.32 0.95 140 16.4 29.5 61.9 4.31 7.83 80° 34.749'W 1.25 2.9 0.42 42.1 0.74 1.35 0.72 121 17.0 29.9 72.8 5.03 7.94 TC3 28° 02.271'N 0.5 3.5 2.11 48.0 0.79 1.31 0.93 141 11.2 29.4 62.9 4.52 7.44 80° 34.831'W ------TC4 28° 02.147'N 0.5 4.0 1.78 44.4 0.70 1.24 0.88 139 11.8 29.3 62.9 4.51 7.35 80° 34.853'W 1.0 2.7 0.35 41.5 0.61 1.27 0.82 142 16.9 30.0 64.3 4.44 7.76 2.0 4.6 0.42 44.9 0.99 1.68 0.82 142 17.4 30.1 48.6 3.33 7.76 2.5 4.8 0.42 49.4 1.30 2.29 0.84 147 17.7 30.2 30.7 2.10 7.68 3.0 64.7 0.22 115 8.72 8.80 0.92 158 17.8 30.3 15.5 1.06 7.60 TC5 28° 01.952'N 0.5 5.6 5.82 56.3 1.35 1.28 1.34 118 0.6 28.3 64.6 5.01 7.31 80° 34.849'W 1.0 7.1 5.15 55.8 1.49 1.45 1.43 121 1.0 28.3 63.5 4.92 7.18 1.5 12.8 0.85 55.2 2.10 2.40 0.78 142 17.3 30.4 35.8 2.45 7.30 2.0 10.0 0.40 47.6 1.69 2.15 0.72 148 17.7 30.4 27.5 1.87 7.57 2.5 34.2 0.35 77.7 5.73 5.59 0.81 150 17.8 30.4 16.5 1.13 7.55 *Sonde

Brevard County: Turkey Creek, September 09, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

Nitrate + ΣN ΣP Alkalinity Water Ammonium Phosphate DOC Temp.* DO* DO* Station Location Nitrite (µg- (µg- (µg- (mg Salinity* pH* Depth (m) (µg-N/L) (µg-P/L) (mg/L) (°C) (%) (mg/L) N/L) N/L) P/L) CaCO3/L) TC1 28° 02.421'N 0.5 36.0 5.8 597 13.9 33.5 11.0 150 16.6 29.6 76.8 5.34 7.92 80° 34.575'W 1.75 47.3 4.9 652 23.6 42.4 8.4 139 17.6 30.0 59.8 4.10 7.88 TC2 28° 02.337'N 0.5 48.9 17.9 715 28.0 40.9 11.4 140 16.4 29.5 61.9 4.31 7.83 80° 34.749'W 1.25 40.3 5.9 590 22.9 41.9 8.6 121 17.0 29.9 72.8 5.03 7.94 TC3 28° 02.271'N 0.5 49.4 29.6 672 24.5 40.6 11.2 141 11.2 29.4 62.9 4.52 7.44 80° 34.831'W ------TC4 28° 02.147'N 0.5 56.3 25.0 623 21.6 38.4 10.6 139 11.8 29.3 62.9 4.51 7.35 80° 34.853'W 1.0 37.4 4.9 582 18.8 39.3 9.9 142 16.9 30.0 64.3 4.44 7.76 2.0 64.3 5.9 629 30.6 52.1 9.8 142 17.4 30.1 48.6 3.33 7.76 2.5 67.0 5.9 692 40.2 70.8 10.1 147 17.7 30.2 30.7 2.10 7.68 3.0 906 3.1 1620 270.0 272.6 11.0 158 17.8 30.3 15.5 1.06 7.60 TC5 28° 01.952'N 0.5 79.1 81.6 789 41.8 39.6 16.1 118 0.6 28.3 64.6 5.01 7.31 80° 34.849'W 1.0 99.3 72.2 782 46.0 44.8 17.2 121 1.0 28.3 63.5 4.92 7.18 1.5 180 11.9 773 64.9 74.4 9.4 142 17.3 30.4 35.8 2.45 7.30 2.0 140 5.6 666 52.4 66.5 8.7 148 17.7 30.4 27.5 1.87 7.57 2.5 479 4.9 1090 177.4 173.1 9.7 150 17.8 30.4 16.5 1.13 7.55 *Sonde

3‐72 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C6 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for September 9, 2015.

Brevard County: Turkey Creek, September 09, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (%) (µM) TC1 28° 02.421'N 0.5 5.7 3.3 16.5 0.46 1.02 5.3 0.8 1.52 28.8 0.136 6.2 24.9 80° 34.575'W 1.75 6.5 4.7 18.0 0.40 1.09 4.3 0.9 1.82 26.9 0.147 6.1 28.5 TC2 28° 02.337'N 0.5 6.6 5.4 10.0 1.16 2.81 5.7 0.9 1.91 25.9 0.143 5.0 23.7 80° 34.749'W 1.25 8.6 5.1 17.5 0.83 1.45 8.4 0.8 2.13 27.7 0.198 5.3 32.5 TC3 28° 02.271'N 0.5 7.5 5.4 12.0 0.82 2.21 4.5 0.9 2.26 28.0 0.176 5.5 29.6 80° 34.831'W ------TC4 28° 02.147'N 0.5 10.8 6.2 14.0 0.57 1.66 3.8 1.1 3.66 36.4 0.328 6.1 47.1 80° 34.853'W 1.0 10.1 5.2 18.0 0.42 0.79 3.2 1.1 3.46 32.6 0.274 6.5 46.9 2.0 8.3 5.5 18.5 0.59 0.96 4.4 1.0 2.66 30.6 0.212 6.7 39.8 2.5 7.7 4.9 18.5 0.42 0.89 3.9 1.0 2.37 35.6 0.229 8.1 44.6 3.0 8.3 28.9 19.0 0.43 0.40 2.4 0.7 1.97 28.7 0.197 6.4 37.8 TC5 28° 01.952'N 0.5 4.3 3.6 <1.0 2.56 6.96 10.1 0.7 0.94 18.7 0.067 5.6 17.3 80° 34.849'W 1.0 4.4 3.4 <1.0 2.90 7.29 9.1 0.7 0.93 17.6 0.064 3.1 9.7 1.5 6.3 4.1 17.0 0.99 2.53 6.2 0.9 1.90 31.2 0.163 7.1 31.7 2.0 4.9 4.4 18.0 1.01 1.85 5.2 0.9 1.41 31.4 0.128 7.6 26.6 2.5 7.6 5.9 19.0 0.61 1.70 3.7 1.2 2.86 29.7 0.187 5.7 30.8 *Refractometer

Brevard County: Turkey Creek, September 09, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) (µg/L)

TC1 28° 02.421'N 0.5 5.7 3.3 16.5 0.46 1.02 5.3 0.8 47.0 28.8 1.6 6.2 348 80° 34.575'W 1.75 6.5 4.7 18.0 0.40 1.09 4.3 0.9 56.3 26.9 1.8 6.1 399 TC2 28° 02.337'N 0.5 6.6 5.4 10.0 1.16 2.81 5.7 0.9 59.1 25.9 1.7 5.0 332 80° 34.749'W 1.25 8.6 5.1 17.5 0.83 1.45 8.4 0.8 66.1 27.7 2.4 5.3 455 TC3 28° 02.271'N 0.5 7.5 5.4 12.0 0.82 2.21 4.5 0.9 70.1 28.0 2.1 5.5 414 80° 34.831'W ------TC4 28° 02.147'N 0.5 10.8 6.2 14.0 0.57 1.66 3.8 1.1 113.5 36.4 3.9 6.1 659 80° 34.853'W 1.0 10.1 5.2 18.0 0.42 0.79 3.2 1.1 107.2 32.6 3.3 6.5 657 2.0 8.3 5.5 18.5 0.59 0.96 4.4 1.0 82.4 30.6 2.5 6.7 557 2.5 7.7 4.9 18.5 0.42 0.89 3.9 1.0 73.4 35.6 2.7 8.1 626 3.0 8.3 28.9 19.0 0.43 0.40 2.4 0.7 61.2 28.7 2.4 6.4 529 TC5 28° 01.952'N 0.5 4.3 3.6 <1.0 2.56 6.96 ### 0.7 29.0 18.7 0.8 5.6 242 80° 34.849'W 1.0 4.4 3.4 <1.0 2.90 7.29 9.1 0.7 28.8 17.6 0.8 3.1 135 1.5 6.3 4.1 17.0 0.99 2.53 6.2 0.9 58.9 31.2 2.0 7.1 445 2.0 4.9 4.4 18.0 1.01 1.85 5.2 0.9 43.7 31.4 1.5 7.6 373 2.5 7.6 5.9 19.0 0.61 1.70 3.7 1.2 88.5 29.7 2.2 5.7 431 * Refractometer

3‐73 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C7. Concentrations of dissolved and particulate parameters for Stations 1-5 for October 14, 2015.

Brevard County: Turkey Creek, October 14, 2015 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammonium Nitrate + ΣN Phosphate ΣP DOC Salinity Temp. DO* DO* Station Location (mg- pH* Depth (m) (µM) Nitrite (µM) (µM) (µM) (µM) (mM) * * (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.417'N 0.5 2.5 0.57 44.3 1.07 1.84 0.90 128 16.4 26.0 67.5 4.99 7.92 80° 34.584'W 1.75 2.5 0.46 41.8 1.17 1.90 0.83 129 17.0 26.3 68.8 5.05 8.07 TC2 28° 02.333'N 0.5 2.5 0.58 44.8 1.24 2.06 0.78 122 16.4 26.1 48.4 3.58 7.80 80° 34.748'W 1.25 2.5 0.51 40.9 1.49 2.25 0.78 131 16.9 26.0 49.8 3.67 7.91 TC3 28° 02.268'N 0.5 2.5 0.46 44.6 1.38 2.16 0.83 130 16.2 26.4 44.2 3.25 7.77 80° 34.829'W ------TC4 28° 02.147'N 0.5 2.1 0.41 41.8 1.38 2.17 0.79 119 16.0 26.3 49.0 3.61 7.54 80° 34.853'W 1.0 2.3 0.53 43.4 1.41 2.24 0.79 131 16.9 26.3 49.9 3.66 7.78 2.0 2.1 0.46 47.3 1.86 2.62 0.76 135 17.2 26.7 38.7 2.82 7.87 2.5 5.2 0.48 43.3 2.51 3.37 0.84 121 17.5 27.0 23.5 1.69 7.78 3.0 46.1 0.54 93.9 7.58 7.80 0.85 133 17.8 27.2 12.1 0.87 7.63 TC5 28° 01.955'N 0.5 5.6 3.37 59.1 1.65 1.65 1.34 150 3.4 25.5 58.4 4.69 7.46 80° 34.854'W 1.0 3.6 0.42 46.5 2.08 2.74 0.84 132 16.9 27.2 46.8 3.38 7.36 2.0 2.7 0.49 43.4 1.98 2.62 0.84 128 17.4 27.2 25.6 1.84 7.67 2.5 5.6 0.45 45.3 2.73 3.33 0.81 129 17.6 27.4 12.2 0.88 7.67 3.0 8.1 5.91 46.7 3.01 3.79 0.76 122 17.6 27.3 8.4 0.60 7.67 *Sonde

Brevard County: Turkey Creek, October 14, 2015 Table 2. Dissolved parameters in g/L.

Nitrate + ΣN ΣP Alkalinity Water Ammonium Phosphat DOC Temp.* DO* DO* Station Location Nitrite (µg- (µg- (µg- (mg Salinity* pH* Depth (m) (µg-N/L) e (µg-P/L) (mg/L) (°C) (%) (mg/L) N/L) N/L) P/L) CaCO3/L) TC1 28° 02.417'N 0.5 35.7 8.0 621 33.2 57.0 10.8 128 16.4 26.0 67.5 4.99 7.92 80° 34.584'W 1.75 34.3 6.5 586 36.1 58.8 10.0 129 17.0 26.3 68.8 5.05 8.07 TC2 28° 02.333'N 0.5 34.3 8.1 627 38.3 63.7 9.4 122 16.4 26.1 48.4 3.58 7.80 80° 34.748'W 1.25 34.3 7.1 573 46.1 69.5 9.4 131 16.9 26.0 49.8 3.67 7.91 TC3 28° 02.268'N 0.5 34.3 6.5 624 42.9 66.9 10.0 130 16.2 26.4 44.2 3.25 7.77 80° 34.829'W ------TC4 28° 02.147'N 0.5 28.9 5.7 585 42.9 67.1 9.5 119 16.0 26.3 49.0 3.61 7.54 80° 34.853'W 1.0 31.7 7.4 608 43.5 69.3 9.5 131 16.9 26.3 49.9 3.66 7.78 2.0 28.9 6.5 663 57.8 81.2 9.1 135 17.2 26.7 38.7 2.82 7.87 2.5 72.8 6.7 607 77.8 104.3 10.1 121 17.5 27.0 23.5 1.69 7.78 3.0 647 7.6 1320 234.7 241.4 10.2 133 17.8 27.2 12.1 0.87 7.63 TC5 28° 01.955'N 0.5 78.3 47.2 828 51.0 51.1 16.1 150 3.4 25.5 58.4 4.69 7.46 80° 34.854'W 1.0 50.9 5.9 652 64.5 84.9 10.1 132 16.9 27.2 46.8 3.38 7.36 2.0 37.2 6.9 608 61.3 81.0 10.1 128 17.4 27.2 25.6 1.84 7.67 2.5 78.3 6.4 635 84.6 103.2 9.7 129 17.6 27.4 12.2 0.88 7.67 3.0 114 82.8 654 93.3 117.5 9.1 122 17.6 27.3 8.4 0.60 7.67 *Sonde

3‐74 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C7 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for October 14, 2015.

Brevard County: Turkey Creek, October 14, 2015 Table 3. Particulate parameters in molar units.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (%) (µM) TC1 28° 02.417'N 0.5 8.4 3.7 17.0 0.73 0.59 4.6 0.8 2.16 35.7 0.250 5.5 33.0 80° 34.584'W 1.75 10.5 4.2 18.0 0.61 0.62 4.2 0.8 2.84 33.0 0.288 5.1 38.1 TC2 28° 02.333'N 0.5 9.8 3.9 17.0 0.61 0.76 4.1 0.8 2.52 33.5 0.273 5.2 36.3 80° 34.748'W 1.25 10.7 4.2 18.0 0.88 1.00 5.5 0.8 2.76 32.0 0.284 5.0 38.1 TC3 28° 02.268'N 0.5 9.9 4.4 17.0 0.82 1.06 3.9 0.9 2.82 35.1 0.290 5.5 38.9 80° 34.829'W ------TC4 28° 02.147'N 0.5 9.8 4.4 18.0 0.77 0.82 4.6 0.8 2.56 34.3 0.280 5.3 37.1 80° 34.853'W 1.0 9.7 4.4 18.0 0.91 0.83 4.5 0.8 2.41 33.4 0.270 5.1 35.4 2.0 8.8 5.0 19.0 0.89 1.18 5.4 0.9 2.46 33.6 0.245 5.9 36.9 2.5 10.8 6.5 19.0 0.40 0.60 2.7 1.0 3.44 32.4 0.290 5.7 43.8 3.0 8.3 27.4 20.0 0.30 0.43 2.4 0.8 2.02 30.8 0.214 5.3 31.5 TC5 28° 01.955'N 0.5 2.7 4.6 3.0 1.86 7.55 6.6 1.0 0.89 23.3 0.052 3.3 6.3 80° 34.854'W 1.0 6.8 4.1 18.0 0.61 1.24 4.2 0.9 1.94 39.2 0.223 7.3 35.7 2.0 8.5 5.4 19.0 0.49 0.74 3.8 0.9 2.58 37.2 0.263 6.7 40.6 2.5 7.5 5.2 19.0 0.36 0.68 2.9 1.0 2.41 35.4 0.220 6.2 33.0 3.0 7.4 5.5 19.0 0.37 0.70 2.7 1.1 2.63 33.9 0.209 6.0 31.7 *Refractometer

Brevard County: Turkey Creek, October 14, 2015 Table 4. Particulate parameters in g/L.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) (µg/L)

TC1 28° 02.417'N 0.5 8.4 3.7 17.0 0.73 0.59 4.6 0.8 66.9 35.7 3.0 5.5 463 80° 34.584'W 1.75 10.5 4.2 18.0 0.61 0.62 4.2 0.8 88.0 33.0 3.5 5.1 534 TC2 28° 02.333'N 0.5 9.8 3.9 17.0 0.61 0.76 4.1 0.8 78.2 33.5 3.3 5.2 508 80° 34.748'W 1.25 10.7 4.2 18.0 0.88 1.00 5.5 0.8 85.4 32.0 3.4 5.0 534 TC3 28° 02.268'N 0.5 9.9 4.4 17.0 0.82 1.06 3.9 0.9 87.3 35.1 3.5 5.5 546 80° 34.829'W ------TC4 28° 02.147'N 0.5 9.8 4.4 18.0 0.77 0.82 4.6 0.8 79.4 34.3 3.4 5.3 519 80° 34.853'W 1.0 9.7 4.4 18.0 0.91 0.83 4.5 0.8 74.8 33.4 3.2 5.1 495 2.0 8.8 5.0 19.0 0.89 1.18 5.4 0.9 76.3 33.6 2.9 5.9 518 2.5 10.8 6.5 19.0 0.40 0.60 2.7 1.0 106.5 32.4 3.5 5.7 613 3.0 8.3 27.4 20.0 0.30 0.43 2.4 0.8 62.5 30.8 2.6 5.3 442 TC5 28° 01.955'N 0.5 2.7 4.6 3.0 1.86 7.55 6.6 1.0 27.5 23.3 0.6 3.3 88.9 80° 34.854'W 1.0 6.8 4.1 18.0 0.61 1.24 4.2 0.9 60.2 39.2 2.7 7.3 500 2.0 8.5 5.4 19.0 0.49 0.74 3.8 0.9 79.9 37.2 3.2 6.7 570 2.5 7.5 5.2 19.0 0.36 0.68 2.9 1.0 74.6 35.4 2.6 6.2 462 3.0 7.4 5.5 19.0 0.37 0.70 2.7 1.1 81.5 33.9 2.5 6.0 444 * Refractometer

3‐75 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C8. Concentrations of dissolved and particulate parameters for Stations 1-5 for November 23, 2015.

Brevard County: Turkey Creek, November 23, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammonium Nitrate + ΣN Phosphate ΣP DOC Temp. DO* DO* Station Location (mg- Salinity* pH* Depth (m) (µM) Nitrite (µM) (µM) (µM) (µM) (mM) * (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.420'N 0.5 2.6 1.87 58.9 0.13 1.27 147 17.2 22.9 83.4 6.50 7.90 80° 34.575'W 1.75 3.3 1.00 60.4 0.17 1.07 135 18.2 23.2 80.4 6.18 7.97 TC2 28° 02.335'N 0.5 2.7 2.08 57.1 0.29 1.23 141 17.1 22.9 74.2 5.78 7.81 80° 34.747'W 1.5 2.8 1.17 59.5 0.10 0.97 138 17.9 23.4 76.2 5.85 8.00 TC3 28° 02.270'N 0.5 2.8 1.45 59.6 0.17 1.03 133 15.8 23.7 7.7 72.80 5.63 80° 34.829'W ------TC4 28° 02.148'N 0.5 2.9 1.49 59.0 0.24 0.96 129 13.2 23.7 68.4 5.37 7.44 80° 34.854'W 1.0 4.1 1.03 61.9 0.18 1.06 132 18.3 24.2 65.2 4.93 7.74 2.0 5.0 1.24 67.0 0.49 1.01 143 18.5 24.4 52.9 3.98 7.85 2.5 7.4 1.03 74.7 1.18 1.12 151 18.5 24.5 47.9 3.60 7.85 3.2 9.9 0.83 87.3 1.76 0.98 146 18.6 24.7 40.1 3.00 7.80 TC5 28° 01.950'N 0.5 4.1 5.34 47.6 1.30 1.02 152 4.2 22.7 69.5 5.86 7.62 80° 34.852'W 1.0 7.2 1.83 71.5 1.27 1.07 143 14.7 24.8 59.9 4.57 7.39 2.0 8.7 1.00 75.9 1.48 0.95 133 18.8 25.0 45.6 3.38 7.72 2.5 11.1 0.83 78.6 2.55 0.96 151 19.0 25.1 29.0 2.14 7.68 2.8 12.8 7.91 82.7 3.25 0.93 136 19.0 25.1 21.1 1.56 7.66 *Sonde

Brevard County: Turkey Creek, November 23, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

Nitrate + DOC Alkalinity Water Ammonium ΣN (µg- Phosphate ΣP (µg- Temp.* DO* DO* Station Location Nitrite (µg- (mg/L (mg Salinity* pH* Depth (m) (µg-N/L) N/L) (µg-P/L) P/L) (°C) (%) (mg/L) N/L) ) CaCO3/L) TC1 28° 02.420'N 0.5 36.0 26.2 825 3.9 0.0 15.2 147 17.2 22.9 83.4 6.50 7.90 80° 34.575'W 1.75 45.6 14.0 846 5.2 0.0 12.8 135 18.2 23.2 80.4 6.18 7.97 TC2 28° 02.335'N 0.5 38.4 29.1 800 9.0 0.0 14.8 141 17.1 22.9 74.2 5.78 7.81 80° 34.747'W 1.5 39.6 16.4 833 3.0 0.0 11.7 138 17.9 23.4 76.2 5.85 8.00 TC3 28° 02.270'N 0.5 39.0 20.3 835 5.2 0.0 12.4 133 15.8 23.7 7.7 72.80 5.63 80° 34.829'W ------TC4 28° 02.148'N 0.5 40.2 20.8 827 7.4 0.0 11.5 129 13.2 23.7 68.4 5.37 7.44 80° 34.854'W 1.0 57.6 14.5 867 5.5 0.0 12.7 132 18.3 24.2 65.2 4.93 7.74 2.0 69.6 17.4 939 15.1 0.0 12.1 143 18.5 24.4 52.9 3.98 7.85 2.5 103 14.5 1050 36.4 0.0 13.5 151 18.5 24.5 47.9 3.60 7.85 3.2 139 11.6 1220 54.5 0.0 11.8 146 18.6 24.7 40.1 3.00 7.80 TC5 28° 01.950'N 0.5 57.6 74.8 667 40.2 0.0 12.3 152 4.2 22.7 69.5 5.86 7.62 80° 34.852'W 1.0 101 25.7 1000 39.3 0.0 12.9 143 14.7 24.8 59.9 4.57 7.39 2.0 121 14.0 1060 45.9 0.0 11.4 133 18.8 25.0 45.6 3.38 7.72 2.5 156 11.6 1100 79.1 0.0 11.5 151 19.0 25.1 29.0 2.14 7.68 2.8 179 110.8 1160 100.7 0.0 11.2 136 19.0 25.1 21.1 1.56 7.66 *Sonde

3‐76 Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute

of Technology Final Report, July 2016

Appendix C8 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for November 23, 2015.

Brevard County: Turkey Creek, November 23, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

PO Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON Station Location Salinity* N Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (µM) (%) TC1 28° 02.420'N 0.5 10.9 6.5 17.0 2.00 2.12 15.0 0.5 1.89 20.9 0.189 4.5 34.9 80° 34.575'W 1.75 18.5 9.9 19.5 3.13 2.58 16.8 0.4 2.33 15.8 0.243 3.2 42.2 TC2 28° 02.335'N 0.5 14.3 6.1 15.0 2.25 2.43 14.9 0.5 2.17 17.3 0.206 3.4 34.6 80° 34.747'W 1.5 42.5 19.7 18.5 2.85 2.96 17.4 0.3 3.98 13.0 0.460 2.2 66.8 TC3 28° 02.270'N 0.5 14.2 5.8 18.0 1.48 1.64 10.8 0.5 2.16 17.5 0.207 3.6 36.6 80° 34.829'W ------TC4 28° 02.148'N 0.5 12.0 6.0 18.0 1.68 1.64 11.2 0.7 2.68 27.2 0.272 5.4 46.4 80° 34.854'W 1.0 13.4 6.2 19.0 1.79 1.86 13.0 0.5 2.34 21.3 0.238 4.3 41.2 2.0 12.6 6.4 19.0 1.97 2.16 14.1 0.5 2.12 20.7 0.218 4.3 38.8 2.5 11.1 6.0 19.0 2.24 2.05 14.8 0.6 2.09 20.9 0.194 4.4 35.0 3.2 10.4 5.8 20.0 1.43 1.97 14.2 0.6 2.08 21.9 0.190 4.4 32.7 TC5 28° 01.950'N 0.5 2.6 2.2 2.0 2.63 5.41 9.1 0.7 0.55 22.0 0.048 4.7 8.8 80° 34.852'W 1.0 8.4 4.5 17.0 1.41 1.88 7.9 0.8 2.26 31.2 0.219 6.6 39.8 2.0 8.0 4.4 20.0 1.76 1.90 11.8 0.7 1.81 25.2 0.168 5.1 29.2 2.5 5.0 3.3 20.0 1.38 1.81 9.6 0.9 1.50 28.2 0.117 5.9 21.0 2.8 5.8 3.8 20.0 1.21 1.42 8.7 0.8 1.49 23.5 0.114 5.1 21.3 *Refractometer

Brevard County: Turkey Creek, November 23, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

Water TSS Turbidit Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) y (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) (µg/L)

TC1 28° 02.420'N 0.5 10.9 6.5 17.0 2.00 2.12 15.0 0.5 58.6 20.9 2.3 4.5 488 80° 34.575'W 1.75 18.5 9.9 19.5 3.13 2.58 16.8 0.4 72.1 15.8 2.9 3.2 591 TC2 28° 02.335'N 0.5 14.3 6.1 15.0 2.25 2.43 14.9 0.5 67.1 17.3 2.5 3.4 485 80° 34.747'W 1.5 42.5 19.7 18.5 2.85 2.96 17.4 0.3 123.3 13.0 5.5 2.2 935 TC3 28° 02.270'N 0.5 14.2 5.8 18.0 1.48 1.64 10.8 0.5 66.9 17.5 2.5 3.6 512 80° 34.829'W ------TC4 28° 02.148'N 0.5 12.0 6.0 18.0 1.68 1.64 11.2 0.7 83.0 27.2 3.3 5.4 650 80° 34.854'W 1.0 13.4 6.2 19.0 1.79 1.86 13.0 0.5 72.5 21.3 2.9 4.3 577 2.0 12.6 6.4 19.0 1.97 2.16 14.1 0.5 65.8 20.7 2.6 4.3 544 2.5 11.1 6.0 19.0 2.24 2.05 14.8 0.6 64.7 20.9 2.3 4.4 491 3.2 10.4 5.8 20.0 1.43 1.97 14.2 0.6 64.6 21.9 2.3 4.4 458 TC5 28° 01.950'N 0.5 2.6 2.2 2.0 2.63 5.41 9.1 0.7 17.1 22.0 0.6 4.7 123 80° 34.852'W 1.0 8.4 4.5 17.0 1.41 1.88 7.9 0.8 70.1 31.2 2.6 6.6 557 2.0 8.0 4.4 20.0 1.76 1.90 11.8 0.7 56.1 25.2 2.0 5.1 408 2.5 5.0 3.3 20.0 1.38 1.81 9.6 0.9 46.4 28.2 1.4 5.9 294 2.8 5.8 3.8 20.0 1.21 1.42 8.7 0.8 46.2 23.5 1.4 5.1 298 * Refractometer

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Appendix C9. Concentrations of dissolved and particulate parameters for Stations 1-5 for December 14, 2015.

Brevard County: Turkey Creek, December 14, 2015 Page 1 of 4 Table 1. Dissolved parameters in molar units.

Alkalinity Water Ammoniu Nitrate + ΣN Phosphat ΣP DOC Temp.* DO* DO* Station Location (mg- Salinity* pH* Depth (m) m (µM) Nitrite (µM) (µM) e (µM) (µM) (mM) (°C) (%) (mg/L) CaCO3/L) TC1 28° 02.419'N 0.5 5.7 0.82 68.4 0.03 0.55 1.42 133 18.1 22.8 94.2 7.32 8.23 80° 34.585'W 2.0 7.1 0.84 69.9 0.08 0.58 1.22 125 19.0 22.8 99.8 7.71 8.33 TC2 28° 02.335'N 0.5 6.5 1.37 68.3 0.08 0.63 1.12 131 14.9 23.1 88.2 6.94 8.05 80° 34.753'W 1.5 7.2 0.92 68.0 0.07 0.66 1.07 122 18.7 22.8 93.8 7.25 8.31 TC3 28° 02.268'N 0.5 6.8 1.07 67.6 0.12 0.64 1.07 128 16.7 23.1 88.1 6.84 8.14 80° 34.832'W ------TC4 28° 02.147'N 0.5 7.4 0.81 70.4 0.27 0.76 1.04 138 16.8 23.2 87.3 6.78 7.92 80° 34.852'W 1.0 10.1 0.90 72.6 0.11 0.68 1.02 126 18.1 23.1 88.4 6.82 8.12 2.0 13.3 0.96 79.0 0.31 0.96 1.16 127 18.4 23.0 89.0 6.87 8.25 2.5 20.2 1.56 96.5 0.65 1.28 1.15 132 18.6 22.8 84.5 6.53 8.18 3.0 35.1 1.65 118 2.03 2.46 1.15 131 18.7 22.8 72.7 5.63 8.07 TC5 28° 01.952'N 0.5 6.6 6.44 60.8 0.77 1.00 1.05 147 3.4 22.7 80.5 6.81 7.57 80° 34.854'W 1.0 14.7 2.73 82.9 0.56 0.98 1.11 136 16.4 23.1 84.9 6.62 7.59 2.0 19.8 1.92 93.3 1.07 1.44 1.17 133 18.6 22.7 85.2 6.60 8.02 2.5 26.7 2.25 99.8 1.77 2.06 1.11 130 18.7 22.6 82.5 6.40 8.03 2.8 25.9 2.29 101 1.78 2.16 1.12 129 18.7 22.6 79.4 6.16 8.02 *Sonde

Brevard County: Turkey Creek, December 14, 2015 Page 2 of 4 Table 2. Dissolved parameters in g/L.

ΣP Alkalinity Water Ammonium Nitrate + ΣN (µg- Phosphate DOC Temp.* DO* DO* Station Location (µg- (mg Salinity* pH* Depth (m) (µg-N/L) Nitrite (µg-N/L) N/L) (µg-P/L) (mg/L) (°C) (%) (mg/L) P/L) CaCO3/L) TC1 28° 02.419'N 0.5 79.3 11.5 959 1.1 17.0 17.0 133 18.1 22.8 94.2 7.32 8.23 80° 34.585'W 2.0 99.0 11.8 979 2.4 17.8 14.7 125 19.0 22.8 99.8 7.71 8.33 TC2 28° 02.335'N 0.5 91.7 19.2 957 2.4 19.4 13.4 131 14.9 23.1 88.2 6.94 8.05 80° 34.753'W 1.5 101 12.9 953 2.0 20.3 12.8 122 18.7 22.8 93.8 7.25 8.31 TC3 28° 02.268'N 0.5 94.8 15.0 947 3.6 20.0 12.8 128 16.7 23.1 88.1 6.84 8.14 80° 34.832'W ------TC4 28° 02.147'N 0.5 103 11.3 986 8.4 23.6 12.5 138 16.8 23.2 87.3 6.78 7.92 80° 34.852'W 1.0 142 12.6 1020 3.3 21.2 12.3 126 18.1 23.1 88.4 6.82 8.12 2.0 186 13.4 1110 9.7 29.7 13.9 127 18.4 23.0 89.0 6.87 8.25 2.5 283 21.9 1350 20.3 39.6 13.8 132 18.6 22.8 84.5 6.53 8.18 3.0 492 23.1 1650 62.8 76.1 13.8 131 18.7 22.8 72.7 5.63 8.07 TC5 28° 01.952'N 0.5 92.4 90.2 850 23.8 30.9 12.6 147 3.4 22.7 80.5 6.81 7.57 80° 34.854'W 1.0 205 38.2 1160 17.4 30.2 13.3 136 16.4 23.1 84.9 6.62 7.59 2.0 277 27.0 1310 33.0 44.6 14.0 133 18.6 22.7 85.2 6.60 8.02 2.5 374 31.5 1400 54.8 63.7 13.3 130 18.7 22.6 82.5 6.40 8.03 2.8 363 32.1 1420 55.2 66.8 13.4 129 18.7 22.6 79.4 6.16 8.02 *Sonde

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Appendix C9 (continued). Concentrations of dissolved and particulate parameters for Stations 1- 5 for December 14, 2015.

Brevard County: Turkey Creek, December 14, 2015 Page 3 of 4 Table 3. Particulate parameters in molar units.

Water TSS Turbidity Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) (NTU) (%) (%) (%) (%) (µM) (%) (mM) (%) (µM) TC1 28° 02.419'N 0.5 6.5 2.3 19.0 1.69 1.65 18.3 0.4 0.78 15.2 0.082 3.4 15.7 80° 34.585'W 2.0 13.3 6.1 20.0 2.17 2.06 20.1 0.3 1.08 12.7 0.141 2.3 21.9 TC2 28° 02.335'N 0.5 9.7 3.6 19.0 2.18 2.12 19.0 0.3 0.84 14.0 0.113 2.6 18.0 80° 34.753'W 1.5 16.1 6.0 20.0 2.12 2.43 19.0 0.2 1.25 12.4 0.167 2.1 24.2 TC3 28° 02.268'N 0.5 7.6 3.4 19.0 2.10 1.97 18.4 0.3 0.64 15.2 0.096 3.1 16.6 80° 34.832'W ------TC4 28° 02.147'N 0.5 8.3 4.5 19.0 2.00 2.05 18.6 0.3 0.72 17.1 0.118 3.4 20.1 80° 34.852'W 1.0 11.0 5.0 19.5 1.90 1.98 20.0 0.3 0.96 15.7 0.143 2.9 22.7 2.0 17.1 8.0 20.0 1.76 2.12 22.3 0.3 1.38 14.3 0.204 2.4 29.3 2.5 17.8 8.1 20.0 2.10 2.22 21.9 0.2 1.33 15.9 0.236 2.7 34.4 3.0 45.0 22.7 20.0 1.21 1.70 22.4 0.2 2.91 14.2 0.532 2.3 73.9 TC5 28° 01.952'N 0.5 2.0 2.5 2.0 2.38 8.21 12.1 0.7 0.44 20.3 0.033 6.1 8.6 80° 34.854'W 1.0 5.9 2.8 18.0 1.47 2.13 19.3 0.4 0.67 19.9 0.098 4.4 18.7 2.0 18.2 8.1 20.0 1.66 1.82 20.8 0.3 1.53 15.8 0.240 2.7 35.1 2.5 15.2 6.7 20.0 1.22 1.84 22.9 0.3 1.37 17.0 0.215 3.0 32.5 2.8 15.3 8.1 20.0 1.28 1.81 22.6 0.3 1.33 16.9 0.215 2.9 31.6 *Refractometer

Brevard County: Turkey Creek, December 14, 2015 Page 4 of 4 Table 4. Particulate parameters in g/L.

Water TSS Turbidit Al Fe Si ΣP ΣP POC POC PON PON Station Location Salinity* Depth (m) (mg/L) y (NTU) (%) (%) (%) (%) (µg/L) (%) (mg/L) (%) (µg/L)

TC1 28° 02.419'N 0.5 6.5 2.3 19.0 1.69 1.65 18.3 0.4 24.0 15.2 1.0 3.4 221 80° 34.585'W 2.0 13.3 6.1 20.0 2.17 2.06 20.1 0.3 33.3 12.7 1.7 2.3 307 TC2 28° 02.335'N 0.5 9.7 3.6 19.0 2.18 2.12 19.0 0.3 26.2 14.0 1.4 2.6 252 80° 34.753'W 1.5 16.1 6.0 20.0 2.12 2.43 19.0 0.2 38.8 12.4 2.0 2.1 339 TC3 28° 02.268'N 0.5 7.6 3.4 19.0 2.10 1.97 18.4 0.3 19.8 15.2 1.2 3.1 232 80° 34.832'W ------TC4 28° 02.147'N 0.5 8.3 4.5 19.0 2.00 2.05 18.6 0.3 22.4 17.1 1.4 3.4 282 80° 34.852'W 1.0 11.0 5.0 19.5 1.90 1.98 20.0 0.3 29.6 15.7 1.7 2.9 318 2.0 17.1 8.0 20.0 1.76 2.12 22.3 0.3 42.8 14.3 2.4 2.4 411 2.5 17.8 8.1 20.0 2.10 2.22 21.9 0.2 41.0 15.9 2.8 2.7 482 3.0 45.0 22.7 20.0 1.21 1.70 22.4 0.2 90.0 14.2 6.4 2.3 1040 TC5 28° 01.952'N 0.5 2.0 2.5 2.0 2.38 8.21 12.1 0.7 13.6 20.3 0.4 6.1 120 80° 34.854'W 1.0 5.9 2.8 18.0 1.47 2.13 19.3 0.4 20.8 19.9 1.2 4.4 261 2.0 18.2 8.1 20.0 1.66 1.82 20.8 0.3 47.4 15.8 2.9 2.7 492 2.5 15.2 6.7 20.0 1.22 1.84 22.9 0.3 42.4 17.0 2.6 3.0 455 2.8 15.3 8.1 20.0 1.28 1.81 22.6 0.3 41.2 16.9 2.6 2.9 442 * Refractometer

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Appendix D: Abstract accepted for Oral Presentation at Ocean Sciences 2016

On behalf of the Program Committee, I am pleased to inform you that the abstract listed below was accepted for presentation at the 2016 Ocean Sciences Meeting in New Orleans, Louisiana. New this year the meeting will begin with a Keynote address by the Honorable Dr. Jane Lubchenco and Icebreaker reception on Sunday, 21 February and conclude at 6:00 PM on 26 February, with a closing poster session and refreshments.

Abstract ID: 92968 Abstract Title: Physical, chemical and biological controls of nutrient fluxes from fine- grained, organic-rich sediments in the Indian River Lagoon, Florida Final Paper Number: MG33A-06 Presentation Type: Oral Session Date and Time: Wednesday, February 24, 2016; 2:00 PM - 4:00 PM Presentation Length: 3:15 PM - 3:30 PM Session Number and Title: MG33A: Physical and Biogeochemical Processes at the Sediment-Water Interface in Estuaries, Coastal Oceans, and Shelf Seas II Location: Ernest N. Morial Convention Center; 231-232

Link to Abstract and Ocean Sciences 2016 websitehttps://agu.confex.com/agu/os16/meetingapp.cgi/Paper/92968

Physical, chemical and biological controls of nutrient fluxes from fine‐grained, organic‐rich sediments in the Indian River Lagoon, Florida Austin L. Fox, John H. Trefry, Robert P. Trocine, Stacey L. Fox Releases and biogeochemical controls of dissolved nitrogen and phosphorus from fine‐grained, organic‐ rich sediments in the Indian River Lagoon, Florida, were determined using (1) interstitial water chemistry, (2) laboratory incubations and experiments and (3) in situ chambers. Fluxes of nitrogen, essentially all as ammonium ions, and phosphorus, essentially all as orthophosphate ions, averaged 2000 ± 1000 and 150 ± 90 µmol/m2/day, respectively. This internal recycling of ammonium and phosphate from fine-grained, organic-rich sediments that compose at least 10% of the sediments throughout the northern lagoon total 300 metric tons/yr and 50 metric tons/yr, respectively, and were greater than external inputs to this system. Ammonium fluxes varied spatially in response to physical and chemical differences in sediment composition. Seasonal and experimental changes in temperature resulted in a >50% differences in fluxes of ammonium and phosphate. High fluxes of dissolved sulfide supported dense mats of sulfur-oxidizing bacteria that provided stability to an otherwise unconsolidated fluff layer; this negative feedback loop reduced the net flux of nitrogen and phosphorus into the overlying water.

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Chapter 4 Movement Measurements of Muck and Fluidized Mud at Dredge Sites

Charles Bostater and Tyler Rotkiske Florida Institute of Technology, Melbourne

4.1. Summary

Muck is typically greater than 75% water by weight (Trefry et al., 1987) and like water, it moves as fluid mud (Mehta et al., 1994) when disturbed by wind waves and currents. The purpose of measuring muck and fluidized mud movement is to provide management information that can be applied to calculate the mass of moving particulate material just above the bottom. This moving dense fluid is a “carrier” of nutrients. Data concerning the magnitude of moving muck and fluid mud in terms of transport fluxes in bottom waters can be used in calibration of sediment and water quality models.

Muck movement and fluxes measured from sonde deployments in Palm Bay and Turkey Creek closely match the magnitude of fluxes reported in previous studies (Mehta et al., 1994; Maglio et al., 2016; Bostater and Rotkiske, 2015). The moving muck and fluid mud collected within the in- situ sondes is in agreement with the definitions used in previous research (Trefry et al., 1987; Teeter et al., 1992; Teeter, 1994; McAnally et al., 2007). At the mouth of Palm Bay, the measurements of moving fluid mud and muck suggest a net westward (upstream) flow and accumulation of moving fluid mud in the southwestern area of Palm Bay (east of US1). This was verified by sludge judge measurements muck depths greater than 3 m. Stokes drift velocity (Craik, 2005) concerning residual upstream bottom transport also supports this westward (upstream) movement of particulates in the bottom boundary layer. The Stokes drift velocity in Palm Bay would be westward due to westward propagating wind driven gravity waves when the wind blows from east to west. Stokes drift theory in shallow bottom waters suggests that moving fluid mud and muck from outer Palm Bay will thus likely contribute to buildup of muck in the deep dredged area east of US1.

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Technology Final Report, July 2016 individual particle settling. Stokes settling law applies only for laminar flows and spherical particles.

The pre-dredging data developed can be used to assess the efficacy of future dredging in terms of muck movement reduction (MMR) by comparing the magnitude of moving muck (1) before dredging, (2) during dredging and (3) after dredging. This procedure has been used in a previous dredging study in the Indian River Lagoon (Maglio et al., 2016; Bostater and Rotkiske, 2015; Rotkiske and Bostater, 2016) to estimate the reduction in moving muck after dredging. In summary, data derived from the sondes can provide important sediment flux (mass transport) of sediments in the bottom boundary layer and the moving lutocline for future bottom sediment forecast modeling.

4.2 Approach

4.2.1 Conceptual Framework, Definitions, Methods

Improving our scientific understanding of estuaries occurs through research, advances in techniques, instrumentation and methods used by scientists (Schubel, 1986). The research reported here concerns direct observation of moving muck and fluidized mud at a dredge site in response to recommendations made by the American Society of Civil Engineers, Task Committee on Management of Fluid Mud (McAnally et al., 2007, I & II). Fluid mud is most often associated with a lutocline and forms in near-bottom aquatic habitats. This mud is a high concentration aqueous suspension of fine sediment and flocs. This fluff and fluidized muck has been defined using site specific density. It is defined as to flow as a density current and is most often associated with navigation and related dredging activities. However, fluid mud is now

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Technology Final Report, July 2016 described as being “ubiquitous” in inland waterways. The fluidization and liquefaction of muck and mud are caused by pore water pressure oscillations due to water waves and associated water surface height amplitude changes. Individual particles are then entrained (Kato and Philips, 1969) within the moving lutocline, and overlying nephelometric water column layers. As noted by the ASCE Task Force, past measurement techniques are characterized as being indirect or surrogate measures, extremely unreliable, not universally applicable, slow, and limited by calibration requirements. They report that new field instruments, techniques and methods development are needed (Waters, 1987; Hydraulics Research Ltd., 1990) and specifically needed is the characterization of fluid mud by temporally averaging the fluid mud sediment fluxes in channels and ports (McAnally et al., 2007).

The research reported below addresses the above recommendations and the approach used makes use of newly developed passive probes or sondes. By definition a sonde is a device that measures a physical property. The conceptual framework used to guide this research concerning fluid mud sediment flux (see Figure 4.1) was previously developed by Mehta et al., 1994 and used during a recent Florida Inland Navigation District dredging project (Bostater and Rotkiske, 2015).

Figure 4.1 Conceptual diagram of the bottom water column based upon previous observations and mathematical models (modified after Mehta, Lee and Li, 1994 and reproduced from Bostater and Rotkiske, 2015).

During the Turkey Creek pre-dredge 2015 research, horizontal measurements of the fluid mud horizontal flux were made within the moving fluid mud layer and moving lutocline. Measurements are time averaged through long term deployments as recommended by McAnally

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Technology Final Report, July 2016 et al., 2009. Vertical fluxes of fluid mud measure upwelling (resuspended) and/or downwelling (depositional) particulate fluxes as reported by Bostater and Yang, 2014 and noted by Di Toro, 2001. The concepts behind directional sediment flux measurements used in this research were also described by Anderson, 1992 where he reports on short or long time interval, directional sediment movement monitoring arrays. These arrays utilize positioning collecting tubes, orifices, funnels, and baffles (that help minimize the effects of turbulence) while measuring large volumes, rate, and the vector (direction and magnitude) of sediment movement carried by currents in remote and inaccessible locations. Sediment flux methods and fluid-mud interactions with water surface wave energy dissipation are topics of research sponsored by the US Office of Naval Research, Coastal Geosciences (Hsu, 2016; Dalrymple, 2006). Bostater and Yang, 2014 described and demonstrated new methods for observations of spectral wave energy in shallow Indian River Lagoon waters and reported on new instrumentation used in this research project for measuring the movement (flux density) of fluid mud and muck.

Published reviews of methodologies and comparisons of reported sediment sampling methods (Gray and Gartner, 2009; Bostater and Rotkiske, 2015; Bostater and Rotkiske, 2016) describe the method type, benefits, and limitations of existing techniques. In general methods have been developed for measuring concentrations of particulate matter and colloidal aggregates, but none were developed for directly measuring the vertical and horizontal fluxes (movement) of fluid mud and muck. Indirect measurement techniques are considered “surrogate” methods and do not conserve mass flux within a control volume since they are typically instantaneous point measurements. It has been reported that measurements of high concentrations of suspended matter using optical backscatter sensors yield noisy calibrations when compared to filtration based techniques. As clearly stated by Bianchi (2007) in-situ investigations of mobile fluid muds within the bottom boundary layer are not possible with conventional equipment using submersible pumps and samplers, CTD, OBS (optical backscattering sensors) and ADPs (acoustic Doppler profilers), since these instruments are too coarse. These systems use only “point” sampling resolutions. Such systems do not allow the reliable calculations of volume mass flux in a conservation of mass form necessary to estimate moving fluid muds necessary for hydrodynamic and scalar substance modeling studies in estuaries. The new method and protocol (Bostater and Rotkiske, 2016) used and described below utilizes direct methods for estimating sediment flux density and has been previously tested and reported.

An essential component of muck removal management and Indian River Lagoon (IRL) restoration is to scientifically understand the movement or “flux” (g m-2 day-1) of the material before, during and after dredging activities This approach allows one to determine the efficacy of the dredging. The purpose of measuring muck and fluidized mud movement is also to provide management information that can be applied to calculate the mass of moving material just above the bottom, as well as re-suspended & settled material (especially at newly dredged locations). This moving material is a “carrier” of nutrients and its understanding will contribute to greater understanding of water quality restoration and management in any modeling framework. The approach is intended to define efficacy of restoration dredging at or near dredged waterways in terms of muck movement reduction (MMR). The goal of this project was (1) to measure in-situ movement (horizontal and vertical) at transects and stations at Palm Bay and Turkey Creek, (2)

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Technology Final Report, July 2016 to collect water samples at the stations and transects and (3) to utilize acoustic and optical floc imaging using the published methods of Bostater and Rotkiske, 2015; Bostater and Yang, 2014.

The above introduction has presented information necessary to help understand the context of this research project from (1) a research perspective and (2) the context of this study from a management perspective.

The conceptual framework and methods for this pre-dredge project were also successfully applied in a Florida Inland Navigation Dredging project in the Indian River Lagoon and reported in Maglio et al., 2016. The sondes and results described by Bostater and Rotkiske, 2015 and Bostater and Rotkiske, 2016 using the sondes shown in Bostater and Yang, 2014 have been shown to measure total particulate matter as: fine sand 500-62 μm, silts 62-4 μm and clays 4- 0.24 μm (as defined by Newcombe, 1996 and the American Geophysical Union’s Subcommittee on Sediment Technology). At stations in the Indian River Lagoon selected sonde sample analyses indicated particles collected were ~80-90% and less than a number 04 sieve (500 micron, 0.0197 in., # 35 mesh) by weight. After rinsing and final settling (~ 5 to 6 hr.) the moving fluid mud particulate matter is greater than 75 % water content and approximately 10- 20% organic matter by weight based upon loss on ignition analysis (105o C drying followed by placement in a furnace at 550o C) as described by Bostater and Rotkiske, 2015. Since the material is greater than 75% water it is considered a non-Newtonian fluid that moves within the lutocline.

The sondes collect moving particles and small floc aggregate particles (after floc disaggregation) with settling velocities ranging from less than 26 to 53 mm sec-1 for fine sands and 3 to 0.044 mm sec-1 for silts and less than 0.011 mm sec-1 for clays based upon the particle characterization information provided by Cooke, et al., 1993. Definitions of fluid mud/muck in this research are also presented in Table 1 (reproduced from Bostater and Rotkiske, 2016).

Table 4.1 Published definitions of fluid mud and muck collected within the sondes (reproduced from Bostater and Rotkiske, 2016).

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The sondes use direct passive sensing and the measurement technique yields a direct measurement of the mean flux (g m-2 t-1) where the mass of the total moving particulate matter is calculated in the laboratory. The area (m2) is based upon the cross-sectional area of the sonde wherein particles enter a fixed control volume. Particles moving into the volume of the sonde have momentum and after entrainment across and through the control surface, momentum is lost due to turbulent dissipation and the particulate matter falls to the lower portion of the control volume. The horizontal sondes are inexpensive and made of PVC fittings that can be anchored to the bottom. The vertical sondes are a type of trap that is based upon larger and similar designs currently used in monitoring fluxes of marine particles and marine snow or flocs (see Bostater and Rotkiske, 2015 for a review). The unit of measurement calculated from these sondes is a time and space averaged mean mass flux density. The sondes essentially measure the total particulate deposition within a control volume.

In ocean and environmental engineering as well as marine science, this depositional flux (mass per unit area per time) is typically calculated from “point measurements “ of the product of velocity U (L/T) and concentration C (M/L3) or UC, where U=characteristic velocity scale, L=characteristic length scale, T=characteristic time scale, M=characteristic mass. However these point measurements are very noisy. By averaging this product over a time period and space (using a cross-sectional area) one obtains what is called an estimate of the mass transport Tm =

AUAA C , where A=cross sectional area, UA=cross sectional averaged velocity and CA=cross sectional averaged concentration (Bostater and Ambrose, ASTM, 1981) and is a standard method used in modeling fate and mass transport (Tm) of chemicals and materials. In this case the total mass transport (Tm) represents the resulting mean horizontal or vertical deposition of particulate matter transported into a sonde control volume V (L3). The above value of the mass transport (Tm) can also be expressed as a time derivative or d(M(t))/dt, where the mass in the sonde volume is M(t) = V . C(t). With a constant control volume with a mass input rate (here the mass input of particles into the sonde volume) the time rate change of mass input rate in the sonde is also given by d(VC(t))/dt = M. This change in mass input rate is also known as a source term M. This relation is also known as a mass balance equation. In the case of the sondes the volume of the sondes are constant and the above can be rewritten as V d(C(t))/dt = W. Thus the mass input rate or flux into the sondes are a function of the integral of d(C(t))/dt where dt = Δt is the deployment time and ∫ 푑푐(t) represents the time integrated input or accumulation of particulate matter in a sonde. This mass input into a sonde is a function of the variable concentration of particles deposited during a deployment period across the fixed sonde cross sectional area and a variable velocity or flow rate.

In summary, with the above definitions, one can note that the sondes passively collect moving fluid mud and muck as a flux of particulate matter during a deployment period Δt.

After the sondes are retrieved laboratory methods are used to analyze the total solids (fluid mud) collected within the sondes. First, the water and solids removed from the sondes are allowed to settle in the laboratory for 24 hrs. The settled sample residue is double rinsed with deionized water to remove dissolved salts. Sample preservation is not practical according to EPA method 160.3 (Total Residue, STORET NO. 00500). The residue is placed into a pre-weighed porcelain evaporating dish and water is decanted using a vacuum tube and/or a syringe or similar device.

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The residue wet volume and wet weight is then measured. Wet density (mg ml-1) is calculated and recorded. Samples are then heated to 105o C until water is evaporated (24 hours is required due to the large quantity of moving fluid mud captured). Final dried residue is weighed and dry total weight of residue (mg) recorded for each sample. Dry weight flux (mass m-2 time-1) is calculated based upon sonde deployment time and the cross-sectional area of the sonde. The dried residue within the evaporating dish is placed in a muffle furnace at 550o C +/- 50o C for one hour. The evaporating dish is then immediately covered, cooled to just above room temperature and re-weighed, and the result is used in the calculation of % loss on ignition (% LOI) in order to provide an estimate of organic matter of the fluid mud collected in a sonde. Linear relations between % LOI and nutrients in the particulate matter (TPN, TPN, and TPC) are then calculated as proposed by Di Toro, 2006 using the relations obtained by Trefry, 2015. Although not calculated, nutrients associated with moving inorganic particulates within the moving fluid mud can thus be estimated to determine nutrients in the moving fluid mud and muck. Sonde mass nutrient fluxes are then calculated using % LOI and the organic weight of each sample. Additional information concerning the above procedures is described in Standard Methods for the Examination of Water & Wastewater (15th ed.) methods 209, A, D, E and ASTM standards C1603-10, STP148E-EB, STP148D-EB and D5907-13.

Triplicate horizontal and duplicate vertical sonde deployments have provided estimates of precision using recommendations published by EPA, 1984. Duplicate and triplicate measurements were made in October 2015. The passive sonde in-situ fluid mud flux measurements are a direct measurement technique. A review of direct and indirect fluid mud movement and flux methods (Bostater and Rotkiske, 2015) indicates that this protocol (Bostater and Rotkiske, 2016) is the only published direct method available for analysis of fluid mud movement or mass flux density (mg cm-2 sec-1) measured in the field.

Directional fluxes of fluid mud are obtained by deploying the horizontal sondes in different directions (E, W, N, S) and the vertical fluxes (depositional and resuspended) are also made by using vertical sonde deployments. The horizontal passive sensing sondes are deployed ~15 to 20 cm off the bottom and have a ~10 cm diameter cross-sectional opening. They are typically placed in E-W and N-S directions or parallel and perpendicular to a waterway. The vertical depositional (settling) and resuspension (upwelling) sondes are placed in pairs near the bottom (~10 cm above). A duplicate pair is also placed 50 cm above the bottom. Thus the lower 0.5 m of the bottom region is sampled. This deployment procedure results in 8 flux measurements to be made at a station location. The heights used were based upon the Hillsboro Bay, Florida, fluidization depths, lutocline and moving lutocline height and model predictions reported by Mehta, et al., 1994) under the influence of water surface wave amplitudes of 2-4 cm. These heights also coincide with waves on lutoclines imaged by acoustic sensors reported by Traykovski, et al., 2000. These are assumed to be representative of conditions in Turkey Creek based upon recent research reported in Bostater and Rotkiske, 2015 in the Indian River Lagoon. The sonde typical deployment period is on the order of 12-17 hours although longer periods (such as over the duration of a wind and/or rainstorm event) can be made. The horizontal systems can be constructed in various sizes.

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The above sonde methods and approach of analysis has been previously used and results reported in Maglio, et al., 2016. An example result from this study is shown in Figure 4.2 below. The figure shows that muck movement reduction (MMR) occurred at transect 4 (upper right) when pre-dredging, during dredging and post-dredging measurements were compared. The data collected during year one at the Turkey Creek stations will be available to make similar comparisons to during dredging and post-dredging research results to quantify muck movement reduction (MMR).

1 - 0.4

day

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VAR_1Pre VAR_2During VAR_3 Post VAR_1 VAR_2 VAR_3 Transect Transect 3 Transect Pre During Post Trial Trial

Figure 4.2 Fluxes in metric tons per day (mT day-1) at locations indicate the fluid mud movement for pre- dredge, during dredging and post dredging conditions obtained from a recent Florida Inland Navigation District dredging project. Results for transect 4 (upper right) indicates muck movement reduction (MMR) occurred during the study near Sebastian Florida during 2015.

Station Selections in Turkey Creek were based upon stratified random sampling and used to determine where the sondes were deployed during (March thru October) 2015 (pre-dredging) as shown in Figure 4.3. Three stations were selected west (upstream) of the Turkey Creek railroad bridge (TCB1 thru TCB3), eight stations were located east of Turkey creek at the mouth (TC1 thru TC6) and two stations were located outside of Turkey Creek (TCOUT1N and TCOUT1S) and eight stations in Turkey Creek east of the US1 bridge. Stations TCP1 thru TCP4 were located near docks/piers around the north and northwest perimeter of Turkey Creek and east of US1 road. Stations TCB4 thru TCB7 were located east of the US1 bridge and on either side of the boating channel within Turkey Creek.

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The rationale for the station locations included the desire to have stations (1) outside of Turkey Creek, (2) stations east of US 1 but within Turkey Creek and (3) stations west of the railroad bridge. In addition, shallow perimeter stations in the vicinity of the north and northwest shore were desired since these are in the Turkey Creek area where biological sampling occurred during year 2015. Stations TCB4 thru TCB7 were selected to be in the vicinity of the boating/waterway channel within Turkey Creek east of US1. A second method was used to compare the sonde method at station TCB6. In addition, stations TCB1 thru TCB3 were sampled twice during the pre-dredge sampling. During the sampling period in October, duplicate vertical flux deployments and triplicate horizontal flux deployments were made following EPA, 1984 recommendations. Overall, the stations were selected in order to perform (1) pre-dredging, (2) during dredging, and (3) post dredging comparisons for assessing muck movement reduction (MMR) as shown in Figure 4.3.

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4.3 Results and Discussion

4.3.1 Sonde Station Deployment Results

Sonde deployments occurred March 5-6, April 10-11, May 14-15 and October 1-3, 2015. Deployment periods ranged from approximately 12 to 39 hours. The sondes were deployed at the end of a day and retrieved during the following morning. At each station the horizontal mud movement probes (up to 4 directions – east, west, north, south) and four vertical probes (2 measuring settling and 2 measuring upwelling (resuspension) were placed at stations during the deployment period. Results are presented below for movement of fluid mud and muck as a dry weight flux, organic matter flux, as well as associated carbon, nitrogen and phosphorus flux estimated from the sondes located within the bottom 0.5 m lutocline and nepheloid water column.

The laboratory analysis of sonde deployments located west of the railroad bridge (TCB1, TCB2, TCB3) indicated a greater westward (upstream) movement of fluidized muck and greater deposition (settling) than resuspension or upwelling (see Figure 4.4 and Figure 4.5). The calculations shown in these figures indicated the mass flux in terms of (mass per unit area per unit time) by extrapolating the deployment time measurements to an annual basis based upon the sonde cross-sectional area. Each bar in the Figure 4.4 represents the total amount of material collected during a deployment in the specified direction. Thus, n=2 for each station. The values shown in Figures 4.4 and 4.5 represent the actual dry weight of mud and muck trapped and then extrapolated to an annual flux at the stations. The sondes were located within the lower 0.5 water column.

Calculations from the deployments at stations outside and east of Palm Bay (TCOUT1N and TCOUT1S) suggest greater particle settling than resuspension - however the horizontal muck movement is greater by an order of magnitude. This suggests the mud and muck may not be accumulating outside of Palm Bay. The sludge judge (push pole) measurements made at stations during pre and post sonde deployments confirmed little or no mud at the 2 stations located outside of Palm Bay in the Indian River Lagoon. These results are expected due to the shallow depths and influence of the wind the wind and associated broad fetch of the IRL.

Horizontal and vertical probes were deployed at 6 locations across the mouth of Palm Bay (TC1, TC2, TC3, TC4, TC5 and TC6). Results from 5 stations are shown in Figures 4.4 and 4.5. Results suggest greater resuspension than deposition at the mouth of Palm Bay and greater westward movement towards Palm Bay of the fluidized muck and mud.

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Figure 4.5 Measured sonde fluid mud mass flux results extrapolated in terms of lbs. m-2 day-1 for 2015 Turkey Creek pre-dredging stations from the red upwelling (resuspension) and downwelling (depositional) sondes. Values shown represent combined surface and bottom probe measurements.

The transect data from all six stations at the mouth of Turkey Creek were combined to estimate the relative order of magnitude of fluid mud movement in the lower 0.5 - meter bottom layer

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Technology Final Report, July 2016 within the lutocline and near bottom nepheloid layer. The depth was selected since the sondes were placed within the bottom water depth layer depicted in Figure 4.6.

On a dry weight basis, the sonde results suggest that ~ 75,000 thousand lbs. yr-1 (~ 93 kg day -1) dry weight fluid mud and muck moves across the mouth of Turkey Creek in the lower 0.5 m depth bottom layer at the mouth of Turkey Creek. Figure 4.6 below depicts this concept of fluid mud and muck movement at a cross sectional area (vertical slice) at the mouth of Turkey Creek.

Figure 4.6 Conceptual bottom lutocline and nepheloid layer (0.5 m deep) through which fluid mud and muck movement was measured using the sondes. The horizontal and vertical sonde measurements allow one to extrapolate the mass movement or flux density – lbs. per year moving through an idealized bottom cross- sectional area (vertical slice) as depicted above.

The above pre-dredging results can form the basis to determine the muck movement reduction after dredging at the mouth of Turkey Creek. As originally proposed, comparisons of the results from the sondes and another method were made. The station used for the comparison (TCB6) was located near the southern shoreline and channel marker as indicated in Figure 4-3. The second method utilized a flat horizontal sonde that can accumulate both settled fluidized muck and horizontal fluidized muck. The trap with a white optically calibrated inner target allows material to accumulate on and within the probe. The results are reported in total mass per unit time trapped within and on the surface of the sonde or probe. The difference between the 2

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Technology Final Report, July 2016 methods developed for estimating the fluidized muck movement in the east and westward directions along the channel and shoreline was less than one order of magnitude.

Subsurface imaging of the particulate material shows the sondes measure particle movement (Bostater and Rotkiske, 2015). Imaging was used to collect video sequences at stations TCB6 and station TCP2. Visual inspection by a diver and video imagery indicated the fluidized particulates entering the sondes are predominantly in the form of flocs and colloidal assemblages – before they settle and break with the sonde control volume.

Figure 4.7 is an image snapshot from a video sequence at station TCP2 along the north western shore of Palm Bay east of US1 in 1.5 to 2-m water depth. Sludge judge (push pole) measurements made before and after deployments at this station indicated muck thickness on the order of 0.5 m. The flocs and colloidal assemblages also settled on top of the sonde and just inside the sonde. The entrance to the westward facing sonde is seen in the image. The fluidized mud and muck move into the sonde in the form of flocs and colloidal assemblages before settling within where they break inside the sonde. After breaking, the flocs are visually indistinguishable from fluid mud and muck.

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Figure 4.8 indicates locations of the three stations west of the railroad bridge in Turkey Creek. During October the three stations were instrumented (TCB1, TCB2, TCB3) from October 1 thru October 3.

Figure 4.8 Stations TB1, TB2 and TB3 station locations in Turkey Creek west of the railroad bridge.

Triplicate deployments were made at the above three stations using westward facing sondes. The triplicate results for the percent loss on ignition (% LOI) analyses from the 3 stations are shown in Figure 4.9. The westward facing sonde results at station TCB1 and TCB2 indicate excellent results with standard deviation of the triplicate deployment results at TCB1 and TCB2 of 1.58 and 2.21 percent respectively and standard error of the mean of 0.91 and 1.28 % respectively. Station TCB3 results indicate greater variability. The westward facing sondes may have been influenced by deployment to close to the nearby island that blocked the downstream flow of particulates. Pooled station results for the eastward facing sondes are shown in Figure 4.9 and indicated higher organic matter content within the moving fluid mud moving upstream (west of the railroad bridge).

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Figure 4.9 above shows the October 1-3 results for % LOI from station TCB1 and TCB2 for the westward facing (downstream flux) sondes. The triplicate result with a coefficient of variability of 0.05 and 0.09 indicate good reproducibility and precision of the horizontal sonde method for % LOI. Station TCB3 results (shown in Figure 4.9) were influenced by close proximity to an island as shown in Figure 4.8 and the coefficient of variability was 0.38 at this station.

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Analysis was performed using information collected from two stations in order to demonstrate how sonde data from this research project can be related to (1) monitoring results by Trefry, 2015 and (2) utilized in water quality modeling activities. Neither of these research efforts measures the ambient movement of fluid mud and muck that is greater than 75% water (Trefry, 1978). Figure 4.11 thru 4.13 shows two stations TCB1 and TCP1 where sampling was conducted for estimation of fluid mud fluxes.

At each station horizontal probes (up to 4 directions) and four vertical probes (2 measuring settling and 2 measuring upwelling or suspension were placed at stations during a 12-17 hour deployment period. Muck movement can be reported in terms of a mass flux (e.g. g m-2 day-1) dry weight. The laboratory analysis of samples collected by the sonde provide an estimate of % loss of ignition (% LOI) by drying the total particulate matter captured at 105o C followed by

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Technology Final Report, July 2016 placement of the material in a furnace at 550o C as described in Standard Methods For Examination of Water & Wastewater, 1980. Figure 4.11 thru Figure 4.13 show results of the LOI for the 2 stations mentioned above, along with ancillary data collected at each station. 2D Graph 1 30 Loss on Ignition %

25 N=6

Data Y 10 5

0 Sonde Total Particulate Matter LOI (%) LOI Matter Particulate SondeTotal 0 Station: Turkey1 Creek Bridge (TCB1) 2 Turkey Creek Bridge 1 X Data

Col 59 Sonde Total Particulate Matter Dry Weight Density: X = 61 gL-1 (43-82) Water Temp 29.50 C Mud Bottom Muck Depth: 20 cm Water Depth: 1.2 m Horizontal Deployment Orientation: 2 - Upstream, Downstream Deposition (settling) sondes: 2 Resuspension (upwelling sondes): 2 Horizontal Water Velocity: ~ 5 cm/sec Deployment ΔT: 17 hours

Figure 4.11 Percent LOI results at station TCB1 from horizontal and vertical sondes.

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Figure 4.13 Station TCP1 % loss on ignition (LOI) results from the horizontal sondes described developed by Bostater & Yang, 2014. The results depicted above indicates the percent organic matter was different based upon the directional movement of the fluid mud, with the greatest organic matter content from material moving from the north and indicated by the size of the blue triangle.

Using a modification of the methodology originally proposed by Di Toro (2001), relations between % LOI, total particulate organic (% TPOC), total particulate phosphorus (% TP), and total particulate nitrogen (% TN) can be used to estimate the depositional fluxes and horizontal fluxes if the particulate matter fluxes from the sondes are available. Research by Trefry, 2015 has developed relations for estimating the % total particulate carbon, % total particulate nitrogen and % total particulate phosphorus based upon the % LOI of muck. Thus, the sonde data collected can be used to estimate not only the fluid mud fluxes but also the associated carbon, phosphorus and nitrogen fluxes associated with the particulate moving fluid mud using the sonde data. These results demonstrate the use of data from this research task for providing information on bottom boundary layer particulate nutrient flux movement in Turkey Creek for use in water quality modeling activities. For example, Figure 4.14 shows the results of calculations using data collected from station TCP1 where the sonde fluid mud results and the Trefry, 2015 relations (indicated in figure 4.13) can be combined in order to calculate nutrient depositional fluxes over idealized model lower grid layers. This example calculation is meant to demonstrate how the sonde flux data, muck nutrient relations and water quality modeling of Turkey Creek can be combined for model calibration purposes.

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Vertical Sonde Particulate Organic Matter Deposition: Example 100x100x0.5 m Model Grid

Using Station TCP1 4/10-11 2015 Vertical Downwelling (settling) sonde DATA

68 g hr-1 Total Particulate Nitrogen Deposition 33 g hr-1 Total Particulate Phosphorus Deposition

1 Kg hr-1 Upper Water Layer POM Deposition

100 m 100 m 0.25 m Lutocline Layer 0.25 m Moving Fluid Mud Layer

Lower Water Layer POM Deposition Total Particulate Phosphorus Deposition 149 g hr-1 Total Particulate Nitrogen Deposition 784 g hr-1

Stations were instrumented just west of the railroad bridge (TCB1, TCB2, TCB3) from October 1 thru October 3. These were instrumented in response to possible upstream water releases in anticipation of an approaching tropical storm. High flows however did not occur during the deployment period. Figure 4.15 shows the provisional flows from the upstream USGS gauging station.

Figure 4.15 Discharge time series during the October, 2015 deployment period.

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Freshwater inflow was actually at a minimum during the instrument deployment and retrieval period from 10/1 to 10/3. During this pre-dredging sampling period a total of 36 sondes were deployed (12 horizontal and 24 vertical sondes) during approximately a 39-hour deployment period. At these stations, muck depth was measured using a sludge judge (muck pole) constructed of clear PVC pipe. Comparison of the water and mud/muck depths between the May and October, 2015 sampling periods is also shown in Table 4.2. Precision estimated from this technique is reported in the QA/QC section of this subtask report. A review of the USGS provisional discharge data earlier in September showed that a large release of water actually occurred mid-September and may have caused the changes in the muck depths and water depths.

4.3.2 Optical and Acoustic Sampling at Selected Stations

Water clarity at the 3 stations was greater than expected with 1 secchi meter depth at all stations on October 1 and October 3. However the bottom 0.5 meter water layer was extremely clear (see Figure 4.16 (right), but with many flocs and colloidal aggregates as shown below. Bottom water salinity at these stations was in the 10-12 psu range and surface waters were around 2 psu. A diver reported a strong thermocline at the 1 m depth. The unique clarity of the bottom layer water at station TCB1 on October 3, 2015 is shown in Figure 4.16 (right) within the bottom 0.5 meter water collected within a clear PVC sludge judge.

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A fixed location, time continuous acoustic fan beam image (Figure 4.16) acquired at station TCB1 indicated oscillating internal nephelometric layers passing through the acoustic (455 MHz) fan beam within the lutocline. The surface of the moving lutocline indicated passing waves as water moved through the fixed station acoustic fan beam.

Similar acoustic backscatter imaging results have been reported by Traykovski et al. 2000 above fluid mud flows and within a moving lutocline. Similar waves in resuspended sediment and nepheloid layers induced by internal solitary waves have also been reported in acoustic echograms and models as shown in Bourgault, et al., 2014.

Analysis of floc movements and sizes were conducted at station TCB1 using imaging methods described by Bostater and Rotkiske, 2015. In-situ imaging of large underwater flocs has also been reported by Eisma et al., 1990 and Manning et al., 2011. At TCB1, Lagrangian movement of the water was measured. Triplicate measurements indicated movement between 30-31 cm sec-1. Image analysis of flocs and colloidal assemblages indicated predominate size range of 0.1 mm to 10.2 mm effective diameter. Mean cross-sectional floc diameter was 2.77 mm (2770 μm) ± 2.44 mm SD with a median floc effective cross-sectional area of 30 mm2. Image analysis of the in-situ flocs and colloidal aggregates in the bottom 20-30 cm water column layer provided estimates of the colloidal aggregate sizes in terms of an effective cross-sectional area (mm2) frequency distribution as shown in Figure 4.17. The size frequency distribution follows an exponential distribution as determined by application of the KS nonparametric test (P<0.001).

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An example image from a 3 channel “multispectral” floc camera system was acquired at station TCB1 as shown in Figure 4.18 below. As noted, the flocs that dominated the particles in the clear high salinity bottom water layer were not spherical in shape and thus settling or vertical deposition rates do not follow terminal gravitational settling based upon spherical Stokes estimation as discussed in Bostater and Rotkiske, 2015. When the floc and colloidal assemblages enter and settle within the sondes they are broken (like snowflakes) and their size and form are not distinguishable from collected fluid mud and muck outside the sonde. These fragile mineral and biogenic aggregates are broken by Niskin bottles and sampling with pumps. Thus they are not typically observed using common water sampling methods (Gibbs and Konwar, 1983).

4.3.3 Wide Area Sonde Data Analyses Results

The pre-dredge sonde deployment results during 2015 have been compared with respect to total non-directional moving particulates in the lutocline (dry weight) extrapolated to grams m2 day-1 from the following areas: (1) stations at the mouth and just outside of Palm Bay (n=52), (2) stations west of the railroad bridge (n=52), and (3) stations east of US1 within Palm Bay (n=54). The distribution of the measured dry weight fluxes are indicated in Figure 4.19. The variability is

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Technology Final Report, July 2016 greater at stations East of US1 within the bay as shown in the figure below. The pooled station results will be available to consider the efficacy of dredging in terms of muck movement reduction (MMR) as shown in Figure 4.2. The data used in Figure 4.19 suggest the fluid mud movement measurement distributions are non-normal. Kruskal-Wallis p test for analysis of variance for n=164 cases and the three grouping categories indicated p-values <0.001, suggesting the centers of the three station grouped distributions are different. Kolmogorov-Smirnov two sample test probabilities were 0.001 or less and suggest the distributions are different from each other. Box plots and interquartile ranges have been used to help identify outliers as described by Goic et al. 2013; Frigge et al. 1989; Iglewicz and Hoaglin, 1993.

Pooled area results suggest the area moving fluid mud fluxes are different (P < 0.001) using the Kolmogorov-Smirnov two sample test. The above total fluxes or fluid mud results will be available for evaluating muck movement reduction (MMR) using the future dredging and post dredging results.

Area wide characterization of subsurface sediment media with different grain size characteristics has been previously studied using GIS techniques. Specifically, Nobre and Sykes, 1992 have demonstrated a power Bayesian kriging technique for mapping subsurface data. The methodology (Bostater and Rotkiske, 2016) maps data in a manner where observational data prevails close to observed stations, but minimizing mapped result errors using variograms and associated variance reduction methods. This technique was applied to develop subsurface fluid mud movement (fluxes) using spatial contours and grids for the Turkey Creek data. Resulting geospatial results are shown in Figures 4.20, 4.21, 4.22, 4.23 and 4.24. Use of this method reduces predicted variable kriging variances by 2-3 orders of magnitude by utilizing Bessel correlation functions of the first kind and Hankel transformations. By using power variograms

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Technology Final Report, July 2016 methods and correlation methods, one can reduce predicted error variance due to automated detection of potential outliers. Figure 4.19 and Figure 4.20 show the subsurface continuous fluid mud movement using the above methodology in order to predict the geospatial subsurface bottom layer distribution of moving fluid mud and muck in Turkey Creek for particulate organic dry weight material and total dry weight fluxes collected. Gridded data in Figures 4.21 thru 4.24 represents georeferenced 6.5 m2 gridded data used to create the color pixel flux maps. Gridded data are used for overlaying with airborne and satellite imagery and to coincide with model grid sizes.

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Figure 4.24 Gridded and contoured georeferenced map of estimated particulate organic carbon flux (g m-2 day- 1) moving in the lower 0.5-m water column based upon total horizontal and vertical sonde data from stations east of US 1 and at the mouth of Turkey Creek. A spatial grid of ~25 m2 is overlaid on the 6.2 m2 gridded image. Subsurface characterization utilizes Bayesian kriging power semivariogram methods (Nobre and Sykes, 1992).

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A high spatial resolution multispectral 3 channel airborne image of Palm Bay collected during January, 2015 is shown Figure 4.25. The image has been analyzed to discriminate or extract subsurface bottom reflectance features using remote sensing methods (Bostater, 2006, 2008, 2012). The effective pixel size or ground sampling distance (GSD) is ≈ 6 cm2, and in general matches the gridded data sizes shown above. The inset in the image shows the top of the channel markers subsurface features in greater detail.

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Section 4.4 Conclusions

 The fluxes measured from sonde deployments closely match the magnitude of fluxes shown in Figure 4.1 and reproduced below. The grey area represents the range of fluxes observed in Turkey Creek during the 2015 research period. Thus fluxes are within the range of previous research results by Mehta et al., 1994 and Bostater and Rotkiske, 2015. This indicates the new sonde methodology is capturing the moving fluid mud in the lutocline.

 The muck and fluid mud collected by the sondes are in agreement with the quantitative definitions published by previous research (Mehta, et al. 1994; Teeter 1992, 1994; McAnally, et al. 2007). The area outline within the yellow box indicates the range of particulate fluxes measured during this project (~ 1 x 10-3 to 0.49 g cm-2 sec-1).

 The total horizontal movement of fluid mud and muck collected by the passive sonde method suggests a net westward flow and moving fluid mud may accumulate and settle in the western areas of Palm Bay (east of US1). This was verified by sludge judge measurements near station TCP4 where in-situ muck depth was greater than 3 m.

 Solids moving in the bottom lutocline and nepheloid layers into the sondes include flocs and colloidal aggregates. These fine grain aggregates were clearly observable in optical and acoustic imagery. Image analysis of flocs and colloidal assemblages indicated predominate sizes ranged from 0.1 mm to 10.2 mm effective diameter. Mean cross-sectional floc diameter was 2.77 mm (2770 μm) ± 2.44 mm SD with a median floc effective cross-sectional area of 30 mm2. The size distribution does not follow the normal distribution. These particulates do no settle

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Technology Final Report, July 2016 according to Stokes settling velocities. In essence, a substantial transport pathway of particulate matter within the moving lutocline is via flocs and colloidal aggregates.

 Area wide station analysis results utilizing all flux density sonde results shown in Figure 19, suggests a significantly different magnitude of material moving (1) west of the railroad bridge, (2) east of US1 and (3) at the mouth and outside of Palm Bay. Fluxes greater than 1200 g m2 day1 were observed with a net flux towards US1 (the western area of Palm Bay). Overall, it appears that Palm Bay may be acting like a muck sink. Both the IRL and Turkey Creek (west of the railroad bridge) appear to be acting as sources of muck.

 Area wide GIS spatial analysis demonstrates that the sonde data can be processed in gridded manner (see Figures 4.20 thru 4.24) that may be readily utilized in water quality and sediment modeling state variables - particulate organic matter, particulate inorganic matter, particulate organic nitrogen, particulate organic phosphorus and organic carbon fluxes.

 On a dry weight basis, total moving muck collected at a transect of six stations across the mouth of Palm Bay indicates 93,151g m-2 day-1 (dry weight) or 0.75 million lbs. m-2 yr-1 of muck moves across the mouth of Palm Bay within the lutocline (the lower 0.5-m water column) as depicted in Figure 4.6. The net westward flux was towards the western area of Palm Bay (east of US1) during the sampling period.

 Although dredge permit delays caused no dredging to occur this research period, the data developed can be used assess the efficacy of dredging in terms of muck movement reduction (MMR) similar to previous research conducted for the Florida Inland Navigation District and depicted in Figure 4.2.

 Area wide data derived from the sondes can provide model calibration sediment movement and mass transport data in the bottom boundary layer and the moving lutocline.

4.5 Quality Assurance Plan for Task 4

A. Project Purpose and intended use of data

The statement of work provided to Brevard County contains information on the purpose and intended use of the data collected in Task 4. In general, the purpose of Task 4 was to collect research data to assess the movement of fluid mud and muck. The scope of work described the probes and sondes to be deployed in order to assess muck movement reduction (MMR) during the pre-dredge, during dredging, and post dredging sampling. Efficacy of the dredging could be

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Technology Final Report, July 2016 inferred by analysis of sonde data in terms of total non-directional flux density (mass per unit area per unit time) – fluid mud and muck movement.

B. Brief historical overview and literature search

Bostater and Yang, 2014; Bostater and Rotkiske, 2015 and Maglio et al., 2016 previously described the sondes (vertical & horizontal). They reviewed existing and historical aquatic methods that might be considered for indirect (surrogate) and direct measurements of fluid mud movement in terms of mass flux density (mass per unit are per unit time). The scientific methods and approaches reported in Bostater and Rotkiske, 2015, presented and compared (1) different operating principles of over 20 different specific samplers, probes and sensor systems applicable to sampling of fluid mud and bottom sediment characteristics, (2) the methodologies were compared as being optical, acoustical or direct and (3) the benefit and limitations of the various methods (particularly bedload type samplers). Only cylindrical sediment traps were noted as being capable of measuring vertical flux density, and that these were used around the world in different configurations by researchers. No horizontal traps were reported in the literature. The review also indicated no direct methods had been developed and reported in the open scientific literature for horizontal and directional fluid mud movements. Only one technique that incorporated directional measurement method has been published in the form of a US patent (Anderson, 1992) but the patent did not address or mention the ability to measure time and spatially averaged horizontal fluxes of particulates using the invention. Figure 4.5.1 below summarizes the theoretical operational basis and field sampling approach of the mass conserving sondes.

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Instantaneous water sample sampling (grab samples) or pumped samples cannot capture the variability of fluxes of substances in waters nor can grab sample results or pumped samples be used to calculate the conservation of mass in time and space that the sondes capture and which point sampling techniques cannot estimate. Maglio, et al., 2016 reported on the use and results to estimate muck movement reduction in Florida waters during a recent dredging project using the sondes and methods proposed for and accepted for use in this project. This research and the sonde operational theory follow the recommendations of the American Society of Civil Engineers (ASCE), Task Committee on Management of Fluid Mud, 2007 concerning the need to develop methods to measure fluid mud using temporal and spatial averaging techniques. No prior US EPA standard method or American Society of Testing and Materials (ASTM) is known to exist concerning direct or indirect (surrogate) horizontal fluid mud movement or flux density (mass L-2 T-1) in aquatic systems.

C. Statement of anticipated results of the research project

The intended use of the data collected in this research is to help assess the benefits of muck dredging in the Indian River Lagoon as part of needed environmental remediation due to impacts of muck on the water quality and biotic populations in the Indian River Lagoon. The expected outcome of the research is to document through research data the reduction in the amount of moving fluid mud and muck after dredging has been completed. The concept of muck movement reduction (MMR) was recently developed for a dredging project in the Sebastian Inlet region and Intracoastal Waterway near Wabasso, Florida. The research demonstrated the ability of the sondes to document muck movement reduction at coastal waterway transects where research monitoring occurred during 2015 (Weaver et al., 2015; Maglio et al., 2016; Bostater and Rotkiske, 2015). Similar to the above referenced dredging project, this research task makes use of stratified random sampling for selection of stations and transects where sonde deployments occur. In addition, stratified random sampling is used to determine when sampling will occur during a selected day. Use of stratified random sampling design for in-situ sampling is intended to remove bias in results that could be attributed to sampling in time and space or locations.

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D. Description of work to be conducted, including the types of analyses to be performed to monitor the effectiveness of the research

Field Sampling:

 Sampling Plan Design and Rationale

The in-situ station sampling design rationale makes use of a stratified random sampling of locations that allows the (1) use of sondes located along transects, (2) stations in the vicinity of shorelines and (3) stations outside the bay (west of the mouth of the bay and upstream of the railroad bridge). This approach allows for the analysis of pre-dredge, during dredging, and post dredging sonde measurements of fluid mud movement in terms of - mass per unit area per unit time.

 Location of each sampling point for the project and link each point to the sampling methods, analysis, indicators, populations to be measured or investigated and frequency.

The map Figure 4.2 shows the location of each sampling point. At each location deployments of the sondes are made. At each location 2 or 4 horizontal directional sondes are deployed. Two along the transect at the mouth of the Turkey Creek measuring inflow and outflow (east-west directions) and two at the 3 stations west of the railroad bridge in Turkey Creek for measuring upstream and downstream (east-west directions). Horizontal sondes deployments at all other stations were in the North, South, East, and West orientation.

Table 4.5.1 Description of samples collected during 2015 at each station.

All of the above stations were selected as being relevant to the purpose and intent of the project. The key parameters necessary to estimate muck movement reduction project goal are derived from the deployment of the vertical sondes and horizontal sondes. Key parameters essential for calculation of direction fluxes (mass m-2 t-1) of fluid mud & muck passively moving into each directional horizontal or vertical sonde (depositional, resuspended matter are: (1) deployment

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time (HH.MM), (2) dry weight (grams), (3) calculation of % loss on ignition (estimation of organic content of the fluid mud and after ignition in a muffle furnace). All other parameters collected are provided as ancillary background information such as depths and water grab samples (salinity, NTU, TSS). Water grab sample results at each station are not used in the calculation of moving fluid mud & muck fluxes. As noted above either 2 or 4 horizontal sondes are deployed and one set of four vertical sondes are deployed at each station. The deployment design allows the estimation of muck movement reduction as reported in Maglio, et al., 2016 using the methods for direct measurement of fluid mud & muck flux in Bostater & Rotkiske, 2015.

 Map of the sampling point locations

The Table below gives the general area, station ID name and latitude longitude information. Stations are relevant for calculation of moving fluid mud flux at the following areas: (1) just west of the railroad bridge, (2) with the bay (east of US 1), and (3) at or near the mouth of Palm Bay.

Table 4.5.2 Station locations (latitude longitude decimal degrees), station ID and region.

Figure 4.5.2 Map of stations for Task 4 and as described in the above table.

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Laboratory Analysis

 Previously published references concerning the sondes, field and laboratory analyses are provided in Bostater and Rotkiske, 2015 and Weaver, et al., 2015. Images of the sondes are published in Bostater and Yang, 2014. Data derived from the devices are independent of any time dependent calibration or standards. The volumes of the sondes are essential the same. The cross-sectional sonde openings (areas) are fixed and identical and only vary depending upon whether the sonde is a vertical or horizontal type. Pre-deployment requires capping as the sonde enters the water. After they are attached to the bottom, caps are removed. A cap is reinserted before sonde retrieval. This insures no mud enters the sonde during the deployment and recovery process.

 Calculations for estimating the moving fluid mud flux after laboratory analyses are complete is described in Figure 4.5.3 below. The instruments and methodology is described in Bostater and Yang, 2014; Bostater and Rotkiske, 2015 and Weaver et al., 2015.

Figure 4.5.3 Method for calculating the moving fluid mud flux density for the horizontal and vertical sondes. The cross-sectional area for the vertical sondes is 20.261 cm2 and the cross-sectional area for the horizontal sondes is 81.073 cm2 (based upon ANSI approved NEIKO Model 01412A Digital Caliper, 0.02 mm Accuracy, 0.01 Digital Resolution).

At each station horizontal probes (up to 4 directions) and four vertical probes (2 measuring settling and 2 measuring upwelling or suspension are deployed at stations for ≈12-40 hours. In

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Technology Final Report, July 2016 order to assess the muck movement, results are reported in terms of a mass flux (e.g. mg m-2 yr-1) dry weight (following drying at 105oC. The laboratory analysis of probe deployments also result in an estimate of % loss of ignition (LOI) based upon drying the total particulate matter captured in the sondes at 105oC (Equatherm Environmental Oven) followed by placement of the material in a furnace (Thermodyne SYBRON Type 4800 furnace) at 550o C) as described in Standard Methods For Examination of Water & Wastewater, 1980. Water grab samples are analyzed in the lab for conductivity, temperature and salinity using a calibrated YSI Model 33 (daily calibrated using LaMotte salinity standards). Total water suspended solids are filtered using Millipore nucleopore MF filters with nominal 0.45 micron pore size membrane filters followed by drying in a desiccator using the methods recommended in Standard Methods, 1980; EPA, 1983 and Grasshoff et al., 1976. These results are not needed to calculate fluxes and are collected as background data useful interpretation and modeling.

Water and total solids (fluid mud) are transferred from sondes by pouring from the horizontal sondes into 1 gallon plastic containers with marked lids with station ID, and material is transferred (within 1-2 hours from collection) to the lab for settling and processing. Water is removed in 24 hours and material settled again in the laboratory for 12 hours. Settled sample residue is rinsed and settled again for 12 hrs. Rinsing with deionized water removes dissolved salts that would influence weight of the particulate matter captured. Sample preservation is not practical according to EPA 1983, method 160.3 (Total Residue, STORET NO. 00500) and Greenberg, et al., 1980 (Standard Methods for Analysis of Water & Wastewater, 14th ed.). Settled fluid mud that has been placed into a pre-weighed porcelain evaporating dish is decanted using a vacuum tube and/or a syringe or similar device and volume and weight recorded for wet weight measurement and volume.

All distilled and deionized water used in the decanting process derived from a Barnstead F- Stream III glass still following by carbon activated filtering.

Filter pads are dried in a desiccator using Drierite desiccant, 8 mesh size (CAS 7778-18-9 and CAS7646-79-9) for 48 hours.

The sonde residue wet volume and wet weights are measured using an open balance, Olhaus Pioneer and Sartorius M prove model with 0.001 g digital scale). Scales are calibrated between measurements and at the beginning of daily use. Scale calibrations make use of TROEMNER calibration standards that follow ISO/IEC standard 17025 and ASTM class 4 standards for balance calibration standards (Certification No. 872685A).

Sonde wet density (mg ml-1) is also calculated and recorded and is an ancillary measurement. Porcelain evaporating dishes are heated at 103-105o C until water is removed (one hour or more).

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Dried residue is weighed and dry weight total residue (mg) recorded for each sample. Dry weight flux (g m-2 time-1) is calculated based upon sonde deployment time and cross-sectional area of the sonde. Dried residue within in an evaporating dish is placed in a muffle furnace at 550o C +/- 50o C for one hour. Evaporating dish is then immediately covered, cooled to just above room temperature and weighed and recorded as oven weight for calculation of % loss on ignition (% LOI) using the same balances in order to provide an estimate of organic matter of the fluid mud flux collected in a sonde. Linear relations between % LOI and nutrients in the particulate matter (TPN, TPN, and TPC) are then calculated as proposed by Di Toro, 2001 using the relations obtained by Trefry (personal communication, 2015). Sonde nutrient fluxes are then calculated using % LOI and the dry weight for each sonde sample. Additional information concerning the relevant procedures are prescribed in Standard Methods for the Examination of Water & Wastewater (Greenberg, et al., 1980), Method 208A, ASTM D1888-1978, ASTM D1069-66, ASTM D509-13 (standard test methods for particulate, nonfilterable solids or residue in water). Triplicate horizontal and duplicate vertical sonde deployments have provided estimates of precision of % LOI and sonde dry weight fluxes and analyzed per guidance from EPA, 1984.

The passive sonde in-situ fluid mud flux measurements are a direct measurement technique. A review of direct and indirect fluid mud movement and flux methods is reported in Bostater and Rotkiske, 2015. No other direct method has been reported in any published literature for analysis of field based moving fluid mud, muck or particulate matter flux collected within a moving lutocline. No correction factors are thus used to correct for laboratory or field measurement bias.

E. Quality Control and Measures (per EPA, 1984)

Accuracy and precision of methods were examined during the study of the push pole measurements of station muck measurements using the push pole or sludge judge technique and the sondes fluid mass flux density. The figure below indicates muck depth changes at stations. During October, three closely space stations east of the railroad bridge in Turkey Creek, yielded measurements (n=6) the mean was 0.765 m, a range of 1.33 m, a standard deviation ± 0.481 m, and a coefficient of variation (CV) of 0.628. The precision (the closeness of data values to each other) estimated as relative standard deviation (standard deviation/mean x 100%) for the October transect (stations TCB1-3) muck depth data is thus 63%. Previous work (Weaver, et al., 2015) shows similar results for muck depth precision using a push pole or sludge judge (1.5 inch diameter clear PVC pipe) and similar replicate sampling technique.

EPA (1984) suggests the use of the sample coefficient of variation (CV – an index of precision and reliability of a measurement system (see Liu, 2012) as a method to address precision of physical measurements. EPA suggested (1984) data quality variability documentation is the purpose of a quality assessment program when considering physical measurement methods and

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Technology Final Report, July 2016 the capability of a measurement system. Boxplots are used to help identify potential outliers (Frigge, Hoaglin and Iglewicz, 1989; Goic et al., 2013; Iglewicz and Hoaglin, 1993).

Figure 4.5.4 shown below and the results above make use of collocated samples (multiple measurements at a point in space and time) and replicates (duplicates and triplicates). Measurements are made immediately before and after sonde deployments for precision evaluation using the sludge judge (push pole method) method as described above.

Precision and reliability estimates based upon triplicate deployments at stations TCB1, TCB2 and TCB3 are shown in the Tables 4.5.3 through Table 4.5.5 below. Organic matter content in terms of % loss on ignition results precision results were 0.05 to 0.09 (coefficient f variation) at 2 stations for horizontal sonde flux triplicate results at stations TCB1 and TCB2 as shown in Table 4.5.3. The % loss on ignition (ash weight or organic matter) suggests good reproducibility between stations and a pooled coefficient of variability of 0.136 or 13.6 %. The % LOI and sonde flux measurements used to calculate the flux of carbon, nitrogen and phosphorus in the moving fluid mud collected within the sondes are described in Figures 4.12 and 4.13.

Table 4.5.4 shows results from triplicate deployments at two stations with a pooled (average) variation of coefficient of 0.195 (19.5 %) for total particulate nitrogen. Similar quality control analyses were applied to the total dry weight horizontal and vertical sonde fluxes results from the two stations where triplicate deployments were made and is shown in Table 4.5.5 and Table 4.5.6 below.

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Table 4.5.3 Triplicate deployment results at three stations for % loss of ignition (% organic matter) within sonde moving fluid mud.

Table 4.5.4 Triplicate deployment results from two stations for moving horizontal sonde fluid mud flux measurements in g m -2 day-1of total organic particulate nitrogen.

Table 4.5.5 Triplicate deployment results from two stations for horizontal sonde moving fluid mud flux dry weight measurements in g m -2 day-1.

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Table 4.5.6 Pooled station duplicate deployment results (TCB1 and TCB2) for vertical sonde particulate flux precision estimates.

Vertical Sonde Dry Weight Flux Precision Estimates (g m-2 min-1 ) Bottom Deposition Top Deposition Bottom Resuspension Top Resuspension Std. Mean Error ± 0.016 ± 0.032 ± 0.0002 ± 0.002 Std. Deviation ± 0.031 ± 0.064 ± 0.003 ± 0.004 Coeff. Of Variation 0.87 1.41 0.85 0.76

Table 4.5.6 shows quality control results in terms of precision estimates for vertical sonde measurements of depositional and resuspended total particulate matter collected at stations TCB1 and TCB2. Total samples (n=4) collected for each of the top and bottom sondes indicate lower precision. These results support prior research suggesting vertical probes, traps and sonde methods result in less reliable estimates of settling and resuspension of particulate matter (Di Toro, 2001).

Quality control estimates obtained from duplicate and triplicate sonde deployments as described above are the only known information available for any indirect or direct method related to measurements of moving fluid mud or muck flux density. Evaluation of the above suggests similar procedures need to be conducted at other stations within the sampling design being used in order to help insure quality indicators are available for Task 4 sonde data.

Task 4 endpoint analyses - data analysis products and interpretation will be based on the documentation of muck movement reduction (MMR) as presented in Figure 4.2 and as reported in Bostater and Rotkiske, 2015, 2016; Weaver et al., 2015, and Maglio et al., 2016.

F. Documentation and Records

Field sampling documentation utilizes field data sheets used to document sampling dates and ancillary data collected at each station. The form used is shown in Figure 4.5.5 and was specifically designed and used in a prior dredging research study where the sondes were deployed and is being used in this research. Station positions were determined using WAAS grade differential GPS receivers. Sheets are placed within a special aluminum page holding notebook in the field to help insure log sheets remain dry in the event of rain and during use. All field records are stored in the Environmental Optics & Remote Sensing Lab, Building 407, on the FIT Campus. All sample records are locked and only available to the PI and working lab and field assistants. Detailed results from sample analyses brought into the lab are recorded in bound notebooks. Selected information is recorded with different weights and volumes necessary for

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Technology Final Report, July 2016 parameter calculations and tracked through the sample processing and data entry process until stored with original field data sheets. Any field or lab deviation or anomaly is recorded on the field sheets and in the bound notebooks and initialized by the PI. Sample bottles and containers are marked in the field as to station ID using waterproof pens/markers on the caps of the containers.

Figure 4.5.5 Example of a field sampling log sheet used to record sonde deployments at each station and any field related information.

Field data are entered into a Microsoft Excel spreadsheet and calculations performed within the project sheets. The spreadsheet is copied and stored on multiple computers and digital storage devices to insure no loss of information may occur due to computer software or hardware problems. Data backups occur monthly. Data analysis is performed using SYSTAT statistical software, ArcGIS geographical information system software, and ENVI image processing software. Monthly reports and quarterly reports utilize the above software. MS Word and PowerPoint are used to produce reports. Data entry is verified from data sheets and lab notebooks.

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G. Training Required For The Project

To date the Principal Investigator has personally trained assistants in the proper deployment of the sondes and their recovery, with special attention given to the insertion and removal of caps in the horizontal sondes to insure no fluid mud or muck enters the sondes during the deployment and retrieval process in the field.

Data Appendices

Appendix I – sonde derived data. Appendix II – background data.

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Weaver, R., Trefry, J., Bostater, C. R., Shenker, J. M., Johnson, K. B., Maglio, C. M. Trocine, R. P., Fox, A. L., Fox, S. L. (2015). Assessment of muck movement, discharge water quality and biological impacts at FIND Dredging Site IR-1: Sebastian River to Wabasso Bridge, Prepared for Florida Inland Navigation District. Project No. ICW-IR-14-01. October 2015.

4-45

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute of

Technology Final Report, July 2016

Appendix 1

Predicte Organic Organic Nitrogen Phosphor Organ Inorg d TPOC Carbon Nitrogen Phosphor Organic Inorga Carbon Mass ous Mass ic anic (%) Eq. Mass Mass ous Mass % % Longitud Dry nic Dry Mass Predicte Predicte Flux Over Flux Over TPN+TPP Matte Matt Name stb Lattitutde Date Time In Date Time Out Used Flux Over Flux Over Flux Over Inorganic Organic e Weight Weigh Flux Over d % TPN d % TPP Sonde Sonde +TPC (g) r Ash er (% Sonde Sonde Sonde Matter Matter (g) t (g) Sonde (g/m2day (g/m2day WT. WT.( Organic- g/(m2 (g/cm2s) (g/cm2s) g/(cm2 s) ) ) (g) g) 0.72)/2.8 day) 8

Out Of The Mouth TC1E 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.367 0.554 13.58611 5.02E-07 5.81E-16 2.557222 0.401722 9.45E-08 1.09E-16 1.48E-08 1.72E-17 0.06072 0.367 0.554 60.15201 39.84799 Into The Mouth TC1W 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.168 0.566 7.697321 1.3E-07 1.51E-16 1.379464 0.283946 2.33E-08 2.7E-17 4.8E-09 5.56E-18 0.015726 0.168 0.566 77.11172 22.88828 Settling Bottom TC1SB 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.054 0.118 10.65116 2.32E-07 2.68E-16 1.970233 0.343023 4.29E-08 4.96E-17 7.46E-09 8.64E-18 0.007001 0.054 0.118 68.60465 31.39535 Settling Top TC1ST 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.027 0.05 11.92532 1.3E-07 1.5E-16 2.225065 0.368506 2.42E-08 2.8E-17 4.01E-09 4.64E-18 0.00392 0.027 0.05 64.93506 35.06494 Upwelling Bottom TC1UB 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 1.621 0.025 33.94485 2.22E-05 2.57E-14 6.62897 0.808897 4.33E-06 5.01E-15 5.28E-07 6.11E-16 0.670814 1.621 0.025 1.518834 98.48117 Upwelling Top TC1UT 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.037 1.63 0.520679 7.76E-09 8.98E-18 0.140414 2.09E-09 2.42E-18 0.000224 0.037 1.63 97.78044 2.219556 Out Of The Mouth TC2E 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.342 0.788 10.25885 3.53E-07 4.09E-16 1.89177 0.335177 6.51E-08 7.54E-17 1.15E-08 1.34E-17 0.042701 0.342 0.788 69.73451 30.26549 Into The Mouth TC2W 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.386 1.109 8.715069 3.39E-07 3.92E-16 1.583014 0.304301 6.15E-08 7.12E-17 1.18E-08 1.37E-17 0.040925 0.386 1.109 74.1806 25.8194 Settling Bottom TC2SB 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.072 0.141 11.48709 3.33E-07 3.86E-16 2.137418 0.359742 6.2E-08 7.18E-17 1.04E-08 1.21E-17 0.010069 0.072 0.141 66.19718 33.80282 Settling Top TC2ST 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.036 0.079 10.61957 1.54E-07 1.78E-16 1.963913 0.342391 2.85E-08 3.3E-17 4.97E-09 5.75E-18 0.004653 0.036 0.079 68.69565 31.30435 Upwelling Bottom TC2UB 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.037 0.008 28.29938 4.22E-07 4.88E-16 5.499877 0.695988 8.2E-08 9.49E-17 1.04E-08 1.2E-17 0.012763 0.037 0.008 17.77778 82.22222 Upwelling Top TC2UT 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.015 0 34.47222 2.08E-07 2.41E-16 6.734444 0.819444 4.07E-08 4.71E-17 4.95E-09 5.73E-18 0.006304 0.015 0 0 100 Out Of The Mouth TC3E 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.39 1.218 8.171434 2.03E-07 2.35E-16 1.474287 0.293429 3.66E-08 4.23E-17 7.28E-09 8.42E-18 0.038763 0.39 1.218 75.74627 24.25373 Into The Mouth TC3W 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.554 1.321 10.00926 3.53E-07 4.08E-16 1.841852 0.330185 6.49E-08 7.51E-17 1.16E-08 1.35E-17 0.067484 0.554 1.321 70.45333 29.54667 Settling Bottom TC3SB 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.076 0.22 8.665165 1.68E-07 1.94E-16 1.573033 0.303303 3.04E-08 3.52E-17 5.86E-09 6.79E-18 0.008012 0.076 0.22 74.32432 25.67568 Settling Top TC3ST 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.027 0.082 8.350917 5.74E-08 6.64E-17 1.510183 0.297018 1.04E-08 1.2E-17 2.04E-09 2.36E-18 0.002743 0.027 0.082 75.22936 24.77064 Upwelling Bottom TC3UB 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.014 0.021 13.63889 4.86E-08 5.62E-17 2.567778 0.402778 9.15E-09 1.06E-17 1.43E-09 1.66E-18 0.002325 0.014 0.021 60 40 Upwelling Top TC3UT 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.02 0.033 12.85273 6.54E-08 7.57E-17 2.410545 0.387055 1.23E-08 1.42E-17 1.97E-09 2.28E-18 0.00313 0.02 0.033 62.26415 37.73585 Out Of The Mouth TC4E 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.684 1.094 13.10771 8.62E-07 9.98E-16 2.461541 0.392154 1.62E-07 1.87E-16 2.58E-08 2.98E-17 0.109176 0.684 1.094 61.52981 38.47019 Into The Mouth TC4W 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.398 1.02 9.49573 3.63E-07 4.21E-16 1.739146 0.319915 6.65E-08 7.7E-17 1.22E-08 1.42E-17 0.045988 0.398 1.02 71.9323 28.0677 Settling Bottom TC4SB 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.201 0.462 10.27665 7.95E-07 9.2E-16 1.895329 0.335533 1.47E-07 1.7E-16 2.59E-08 3E-17 0.02514 0.201 0.462 69.68326 30.31674 Settling Top TC4ST 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.043 0.027 21.07937 3.49E-07 4.04E-16 4.055873 0.551587 6.71E-08 7.77E-17 9.12E-09 1.06E-17 0.011045 0.043 0.027 38.57143 61.42857 Upwelling Bottom TC4UB 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.031 0.001 33.38715 3.98E-07 4.61E-16 6.517431 0.797743 7.77E-08 9E-17 9.51E-09 1.1E-17 0.012618 0.031 1E-03 3.125 96.875 Upwelling Top TC4UT 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.024 0.005 28.48563 2.63E-07 3.04E-16 5.537126 0.699713 5.11E-08 5.92E-17 6.46E-09 7.48E-18 0.008333 0.024 0.005 17.24138 82.75862 Out Of The Mouth TC5E 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.093 2.154 1.187101 1.12E-08 1.29E-17 0.07742 0.153742 7.28E-10 8.43E-19 1.45E-09 1.67E-18 0.001319 0.093 2.154 95.86115 4.138852 Into The Mouth TC5W 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.488 1.313 9.158353 4.52E-07 5.23E-16 1.671671 0.313167 8.25E-08 9.55E-17 1.55E-08 1.79E-17 0.054379 0.488 1.313 72.90394 27.09606 Settling Bottom TC5SB 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.069 0.238 7.554017 2.11E-07 2.44E-16 1.350803 0.28108 3.77E-08 4.36E-17 7.85E-09 9.08E-18 0.006338 0.069 0.238 77.52443 22.47557 Settling Top TC5ST 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.041 0.217 5.267873 8.74E-08 1.01E-16 0.893575 0.235357 1.48E-08 1.72E-17 3.9E-09 4.52E-18 0.002623 0.041 0.217 84.10853 15.89147 Upwelling Bottom TC5UB 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.023 0.029 15.10791 1.41E-07 1.63E-16 2.861581 0.432158 2.66E-08 3.08E-17 4.02E-09 4.65E-18 0.004232 0.023 0.029 55.76923 44.23077 Upwelling Top TC5UT 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.025 0.037 13.7509 1.39E-07 1.61E-16 2.590179 0.405018 2.62E-08 3.03E-17 4.1E-09 4.74E-18 0.004187 0.025 0.037 59.67742 40.32258 Out Of The Mouth TC6E 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.245 1.003 6.566462 1.65E-07 1.91E-16 1.153292 0.261329 2.89E-08 3.35E-17 6.55E-09 7.59E-18 0.019554 0.245 1.003 80.36859 19.63141 Into The Mouth TC6W 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.265 1.058 6.704942 1.82E-07 2.11E-16 1.180988 0.264099 3.2E-08 3.71E-17 7.16E-09 8.29E-18 0.021598 0.265 1.058 79.96977 20.03023 Settling Bottom TC6SB 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.071 0.143 11.26999 3.28E-07 3.79E-16 2.093998 0.3554 6.09E-08 7.05E-17 1.03E-08 1.2E-17 0.009741 0.071 0.143 66.82243 33.17757 Settling Top TC6ST 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.041 0.063 13.43857 2.26E-07 2.61E-16 2.527714 0.398771 4.24E-08 4.91E-17 6.7E-09 7.75E-18 0.00671 0.041 0.063 60.57692 39.42308 Upwelling Bottom TC6UB 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.035 0.074 10.89934 1.56E-07 1.81E-16 2.019867 0.347987 2.9E-08 3.35E-17 4.99E-09 5.77E-18 0.004644 0.035 0.074 67.88991 32.11009 Upwelling Top TC6UT 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.024 0.043 12.18781 1.2E-07 1.39E-16 2.277562 0.373756 2.24E-08 2.59E-17 3.67E-09 4.25E-18 0.003561 0.024 0.043 64.1791 35.8209 North TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.204 1.845 3.206971 7.83E-08 9.07E-17 0.481394 0.194139 1.18E-08 1.36E-17 4.74E-09 5.49E-18 0.00792 0.204 1.845 90.04392 9.956076 South TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.144 0.974 4.222272 7.28E-08 8.43E-17 0.684454 0.214445 1.18E-08 1.37E-17 3.7E-09 4.28E-18 0.007374 0.144 0.974 87.11986 12.88014 Out Of The Mouth TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.278 0.927 7.760604 2.58E-07 2.99E-16 1.392121 0.285212 4.63E-08 5.36E-17 9.5E-09 1.1E-17 0.026237 0.278 0.927 76.92946 23.07054 Into The Mouth TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.208 1.514 3.94409 9.82E-08 1.14E-16 0.628818 0.208882 1.57E-08 1.81E-17 5.2E-09 6.02E-18 0.009946 0.208 1.514 87.92102 12.07898 Settling Bottom TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.119 0.854 3.996603 2.28E-07 2.64E-16 0.639321 0.209932 3.65E-08 4.22E-17 1.2E-08 1.39E-17 0.005767 0.119 0.854 87.76978 12.23022 Settling Top TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.016 0.118 3.895937 2.99E-08 3.46E-17 0.619187 0.207919 4.75E-09 5.49E-18 1.59E-09 1.85E-18 0.000756 0.016 0.118 88.0597 11.9403 Upwelling Bottom TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.009 0.883 0.100336 4.33E-10 5.01E-19 0.132007 5.69E-10 6.59E-19 8.32E-06 0.009 0.883 98.99103 1.008969 Upwelling Top TCOUT1N 28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.037 0.011 26.51505 4.7E-07 5.44E-16 5.143009 0.660301 9.12E-08 1.06E-16 1.17E-08 1.35E-17 0.011958 0.037 0.011 22.91667 77.08333 North TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.233 1.256 5.183363 1.45E-07 1.68E-16 0.876673 0.233667 2.46E-08 2.84E-17 6.55E-09 7.58E-18 0.014664 0.233 1.256 84.35191 15.64809 South TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.164 1.291 3.663708 7.23E-08 8.37E-17 0.572742 0.203274 1.13E-08 1.31E-17 4.01E-09 4.64E-18 0.007281 0.164 1.291 88.72852 11.27148 Out Of The Mouth TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.195 1.235 4.484848 1.05E-07 1.22E-16 0.73697 0.219697 1.73E-08 2E-17 5.16E-09 5.97E-18 0.010611 0.195 1.235 86.36364 13.63636 Into The Mouth TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.173 1.11 4.431952 9.23E-08 1.07E-16 0.72639 0.218639 1.51E-08 1.75E-17 4.55E-09 5.27E-18 0.009302 0.173 1.11 86.51598 13.48402 Settling Bottom TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.039 0.395 2.8702 5.39E-08 6.24E-17 0.41404 0.187404 7.78E-09 9E-18 3.52E-09 4.07E-18 0.001354 0.039 0.395 91.01382 8.986175 Settling Top TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.084 0.12 14.04739 5.68E-07 6.58E-16 2.649477 0.410948 1.07E-07 1.24E-16 1.66E-08 1.92E-17 0.014371 0.084 0.12 58.82353 41.17647 Upwelling Bottom TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.007 0.016 10.31763 3.48E-08 4.03E-17 1.903527 0.336353 6.42E-09 7.43E-18 1.13E-09 1.31E-18 0.000879 0.007 0.016 69.56522 30.43478 Upwelling Top TCOUT1S 28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.034 0.015 23.84297 3.9E-07 4.52E-16 4.608594 0.606859 7.55E-08 8.73E-17 9.94E-09 1.15E-17 0.00988 0.034 0.015 30.61224 69.38776 Out Of The Mouth TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.116 0.379 7.886925 1.11E-07 1.28E-16 1.417385 0.287738 1.99E-08 2.3E-17 4.04E-09 4.67E-18 0.011127 0.116 0.379 76.56566 23.43434 Into The Mouth TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.065 0.357 5.09821 4.01E-08 4.64E-17 0.859642 0.231964 6.76E-09 7.82E-18 1.82E-09 2.11E-18 0.004023 0.065 0.357 84.59716 15.40284 Settling Bottom TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.075 0.208 8.952002 3.25E-07 3.76E-16 1.6304 0.30904 5.92E-08 6.85E-17 1.12E-08 1.3E-17 0.008169 0.075 0.208 73.49823 26.50177 Settling Top TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.009 0.097 2.698113 1.18E-08 1.36E-17 0.379623 0.183962 1.65E-09 1.91E-18 8.01E-10 9.27E-19 0.000294 0.009 0.097 91.50943 8.490566 Upwelling Bottom TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.032 0.248 3.718254 5.76E-08 6.66E-17 0.583651 0.204365 9.04E-09 1.05E-17 3.16E-09 3.66E-18 0.001442 0.032 0.248 88.57143 11.42857 Upwelling Top TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.047 181.0772 4.12E-06 4.77E-15 36.05543 3.751543 8.2E-07 9.49E-16 8.53E-08 9.87E-17 0.103816 0.047 Out Of The Mouth TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.047 0.271 4.881901 2.77E-08 3.21E-17 0.81638 0.227638 4.64E-09 5.37E-18 1.29E-09 1.5E-18 0.002785 0.047 0.271 85.22013 14.77987 Into The Mouth TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.129 0.377 8.602108 1.34E-07 1.55E-16 1.560422 0.302042 2.43E-08 2.82E-17 4.71E-09 5.45E-18 0.013499 0.129 0.377 74.50593 25.49407 Settling Bottom TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.041 0.034 18.73148 3.72E-07 4.3E-16 3.586296 0.50463 7.11E-08 8.23E-17 1E-08 1.16E-17 0.009357 0.041 0.034 45.33333 54.66667 Settling Top TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.098 0.048 23.0567 1.09E-06 1.27E-15 4.451339 0.591134 2.11E-07 2.44E-16 2.8E-08 3.24E-17 0.027537 0.098 0.048 32.87671 67.12329 Upwelling Bottom TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.059 0.014 27.81317 7.94E-07 9.19E-16 5.402633 0.686263 1.54E-07 1.79E-16 1.96E-08 2.27E-17 0.020002 0.059 0.014 19.17808 80.82192 Out Of The Mouth TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 5.061 0.291 32.5843 1.98E-05 2.3E-14 6.35686 0.781686 3.87E-06 4.48E-15 4.76E-07 5.51E-16 2.010373 5.061 0.291 5.43722 94.56278 Into The Mouth TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 0.136 0.376 8.97309 1.47E-07 1.7E-16 1.634618 0.309462 2.68E-08 3.1E-17 5.06E-09 5.86E-18 0.014847 0.136 0.376 73.4375 26.5625 Settling Bottom TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 1.071 0.773 19.91676 1.03E-05 1.19E-14 3.823351 0.528335 1.97E-06 2.28E-15 2.72E-07 3.15E-16 0.259915 1.071 0.773 41.91974 58.08026 Settling Top TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 0.032 0.318 2.924603 4.51E-08 5.22E-17 0.424921 0.188492 6.55E-09 7.58E-18 2.9E-09 3.36E-18 0.001132 0.032 0.318 90.85714 9.142857 Upwelling Top TCB3 28.036151 -80.5797 4/10/2015 15:15 4/11/2015 8:20 0 0.006 0 0 0.125 0 0 0 0 0 0 0.006 100 0 Into The Mouth TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.784 3.164 6.645193 6.49E-07 7.51E-16 1.169039 0.262904 1.14E-07 1.32E-16 2.57E-08 2.97E-17 0.063325 0.784 3.164 80.14184 19.85816 Settling Bottom TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.384 1.033 9.159551 4.38E-07 5.07E-16 1.67191 0.313191 8E-08 9.26E-17 1.5E-08 1.73E-17 0.042795 0.384 1.033 72.90049 27.09951 Settling Top TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.053 0.156 8.555157 2.26E-07 2.62E-16 1.551031 0.301103 4.1E-08 4.74E-17 7.96E-09 9.21E-18 0.005516 0.053 0.156 74.64115 25.35885 Upwelling Bottom TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.121 0.171 14.13832 8.53E-07 9.87E-16 2.667664 0.412766 1.61E-07 1.86E-16 2.49E-08 2.88E-17 0.020835 0.121 0.171 58.56164 41.43836 Upwelling Top TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.95 0.049 32.76913 1.55E-05 1.8E-14 6.393826 0.785383 3.03E-06 3.5E-15 3.72E-07 4.31E-16 0.379509 0.95 0.049 4.904905 95.0951 Out Of The Mouth TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.156 0.565 7.262714 1.36E-07 1.58E-16 1.292543 0.275254 2.43E-08 2.81E-17 5.17E-09 5.98E-18 0.013776 0.156 0.565 78.36338 21.63662 Into The Mouth TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.284 2.413 3.406326 1.16E-07 1.35E-16 0.521265 0.198127 1.78E-08 2.06E-17 6.77E-09 7.84E-18 0.011717 0.284 2.413 89.46978 10.53022 Settling Bottom TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.042 0.389 3.133604 6.34E-08 7.33E-17 0.466721 0.192672 9.44E-09 1.09E-17 3.9E-09 4.51E-18 0.001593 0.042 0.389 90.25522 9.74478 Settling Top TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.054 0.057 16.64189 4.33E-07 5.01E-16 3.168378 0.462838 8.24E-08 9.54E-17 1.2E-08 1.39E-17 0.010947 0.054 0.057 51.35135 48.64865 Upwelling Bottom TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.072 0.344 5.759615 2E-07 2.31E-16 0.991923 0.245192 3.44E-08 3.98E-17 8.5E-09 9.84E-18 0.005038 0.072 0.344 82.69231 17.30769 Upwelling Top TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.798 0.707 18.16085 6.98E-06 8.08E-15 3.472171 0.493217 1.33E-06 1.54E-15 1.9E-07 2.19E-16 0.176567 0.798 0.707 46.97674 53.02326 Out Of The Mouth TCB7 28.038323 -80.5797 4/10/2015 15:40 4/11/2015 9:30 0.525 2.76 5.299214 3.21E-07 3.71E-16 0.899843 0.235984 5.45E-08 6.3E-17 1.43E-08 1.65E-17 0.033784 0.525 2.76 84.01826 15.98174 Into The Mouth TCB7 28.038323 -80.5797 4/10/2015 15:40 4/11/2015 9:30 0.434 2.141 5.602211 2.8E-07 3.24E-16 0.960442 0.242044 4.81E-08 5.56E-17 1.21E-08 1.4E-17 0.029532 0.434 2.141 83.14563 16.85437 Upwelling Top TCB7 28.038323 -80.5797 4/10/2015 15:40 4/11/2015 9:30 0.015 0.044 8.577684 1.48E-08 1.72E-17 1.555537 0.301554 2.69E-09 3.11E-18 5.21E-10 6.04E-19 0.001565 0.015 0.044 74.57627 25.42373

4-46

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute of

Technology Final Report, July 2016

Appendix 1 (continued)

Out Of The Mouth TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.328 1.69 5.393652 2.13E-07 2.46E-16 0.91873 0.237873 3.63E-08 4.2E-17 9.39E-09 1.09E-17 0.021485 0.328 1.69 83.74628 16.25372 Into The Mouth TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.784 3.164 6.645193 6.27E-07 7.26E-16 1.169039 0.262904 1.1E-07 1.28E-16 2.48E-08 2.87E-17 0.063325 0.784 3.164 80.14184 19.85816 Settling Bottom TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.085 0.744 3.31018 1.35E-07 1.57E-16 0.502036 0.196204 2.05E-08 2.38E-17 8.03E-09 9.29E-18 0.003407 0.085 0.744 89.74668 10.25332 Settling Top TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.009 0.097 2.698113 1.17E-08 1.35E-17 0.379623 0.183962 1.65E-09 1.9E-18 7.97E-10 9.23E-19 0.000294 0.009 0.097 91.50943 8.490566 Upwelling Bottom TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.218 16.891 0.192425 2.02E-08 2.34E-17 0.133848 1.41E-08 1.63E-17 0.000446 0.218 16.89 98.72582 1.274183 Upwelling Top TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.06 0.547 3.18218 9.19E-08 1.06E-16 0.476436 0.193644 1.38E-08 1.59E-17 5.59E-09 6.48E-18 0.002311 0.06 0.547 90.11532 9.884679 North + TCB5N 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 7.031 0.329 32.9201 1.96E-05 2.27E-14 6.42402 0.788402 3.83E-06 4.43E-15 4.7E-07 5.44E-16 2.821718 7.031 0.329 4.470109 95.52989 South- TCB5S 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.385 0.999 9.409 3.07E-07 3.55E-16 1.7218 0.31818 5.62E-08 6.5E-17 1.04E-08 1.2E-17 0.044079 0.385 0.999 72.18208 27.81792 East + TCB5E 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.164 0.773 5.827315 3.24E-07 3.75E-16 1.005463 0.246546 5.59E-08 6.47E-17 1.37E-08 1.59E-17 0.01161 0.164 0.773 82.49733 17.50267 West - TCB5W 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.551 1.75 8.064622 1.51E-06 1.74E-15 1.452924 0.291292 2.72E-07 3.14E-16 5.44E-08 6.3E-17 0.054047 0.551 1.75 76.05389 23.94611 Settling Bottom TCB5 Sett Bott28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.236 1.263 5.216607 4.18E-07 4.83E-16 0.883321 0.234332 7.07E-08 8.18E-17 1.88E-08 2.17E-17 0.014949 0.236 1.263 84.25617 15.74383 Settling Top TCB 5 Sett Top28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.034 2.287 0.258641 2.98E-09 3.45E-18 0.135173 1.56E-09 1.8E-18 9.71E-05 0.034 2.287 98.53511 1.464886 Upwelling Bottom TCB 5Up Bott28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.021 0.098 5.877451 4.19E-08 4.85E-17 1.01549 0.247549 7.23E-09 8.37E-18 1.76E-09 2.04E-18 0.0015 0.021 0.098 82.35294 17.64706 Upwelling Top TCB5 Up Top28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0 0.025 0 0 0.125 0 0 0 0 0 0 0.025 100 0 North TCP1 N 28.038801 -80.5803 5/14/15 5:20 PM 5/15/2015 15:45 6.041 1.196 28.73396 1.59E-05 1.84E-14 5.586793 0.704679 3.1E-06 3.58E-15 3.9E-07 4.52E-16 2.115887 6.041 1.196 16.52618 83.47382 South TCP1S 28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 1 17.955 1.581824 1.45E-07 1.68E-16 0.156365 0.161636 1.43E-08 1.66E-17 1.48E-08 1.72E-17 0.018998 1 17.96 94.72435 5.275653 East TCP1 E 28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 3.399 5.822 12.54914 1.57E-05 1.81E-14 2.349827 0.380983 2.93E-06 3.39E-15 4.75E-07 5.5E-16 0.519365 3.399 5.822 63.13849 36.86151 West TCP1W 28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 1.121 3.26 8.634641 3.55E-06 4.11E-15 1.566928 0.302693 6.45E-07 7.46E-16 1.25E-07 1.44E-16 0.117753 1.121 3.26 74.41223 25.58777 Settling Top TCP1 Sett Top28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.042 0.269 4.439175 6.84E-08 7.92E-17 0.727835 0.218783 1.12E-08 1.3E-17 3.37E-09 3.9E-18 0.002262 0.042 0.269 86.49518 13.50482 Settling Bottom TCP1 Sett Bott28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 1.015 4.833 5.776514 2.15E-06 2.49E-15 0.995303 0.24553 3.71E-07 4.29E-16 9.15E-08 1.06E-16 0.071226 1.015 4.833 82.64364 17.35636 Upwelling Bottom TCP1 Up Bott28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.017 0.067 6.777116 4.23E-08 4.89E-17 1.195423 0.265542 7.46E-09 8.63E-18 1.66E-09 1.92E-18 0.0014 0.017 0.067 79.7619 20.2381 Upwelling Top TCP1 Up Top28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.01 0.027 9.134384 3.35E-08 3.88E-17 1.666877 0.312688 6.12E-09 7.08E-18 1.15E-09 1.33E-18 0.001111 0.01 0.027 72.97297 27.02703 North TCP2N 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 1.462 0.611 24.23813 3.39E-06 3.92E-15 4.687626 0.614763 6.55E-07 7.58E-16 8.59E-08 9.95E-17 0.431882 1.462 0.611 29.47419 70.52581 South TCP2S 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 1.232 4.588 7.100134 8.36E-07 9.68E-16 1.260027 0.272003 1.48E-07 1.72E-16 3.2E-08 3.71E-17 0.106348 1.232 4.588 78.83162 21.16838 Settling Top TCP2E 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.296 1.109 7.065144 8E-07 9.26E-16 1.253029 0.271303 1.42E-07 1.64E-16 3.07E-08 3.56E-17 0.025425 0.296 1.109 78.93238 21.06762 West TCP2W 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.861 0.004 34.31166 1.13E-05 1.31E-14 6.702331 0.816233 2.21E-06 2.56E-15 2.69E-07 3.11E-16 0.360158 0.861 0.004 0.462428 99.53757 Settling Bottom TCP2 Sett Bott28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.091 13.362 0.129697 4.52E-09 5.23E-18 . 0.091 13.36 99.32357 0.676429 Settling Top TCP2 Sett Top28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.022 0.129 4.808867 4.05E-08 4.68E-17 0.801773 0.226177 6.75E-09 7.81E-18 1.9E-09 2.2E-18 0.001284 0.022 0.129 85.43046 14.56954 Upwelling Down TCP2 Up Down28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.002 0.162 0.173442 1.33E-10 1.54E-19 0.133469 1.02E-10 1.18E-19 . 0.002 0.162 98.78049 1.219512 Upwelling Top TCP2 Up Top28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.425 0.096 28.07427 4.57E-06 5.28E-15 5.454854 0.691485 8.87E-07 1.03E-15 1.12E-07 1.3E-16 0.145438 0.425 0.096 18.4261 81.5739 North TCP3N 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.764 0.17 28.15233 2.08E-06 2.41E-15 5.470466 0.693047 4.04E-07 4.68E-16 5.12E-08 5.93E-17 0.262173 0.764 0.17 18.20128 81.79872 South TCP3S 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.007 2.282 0.127124 8.61E-11 9.96E-20 0.007 2.282 99.69419 0.30581 East TCP3E 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.205 0.973 5.792492 4.6E-07 5.32E-16 0.998498 0.24585 7.92E-08 9.17E-17 1.95E-08 2.26E-17 0.014426 0.205 0.973 82.59762 17.40238 West TCP3W 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.276 1.226 6.130382 6.55E-07 7.58E-16 1.066076 0.252608 1.14E-07 1.32E-16 2.7E-08 3.12E-17 0.020559 0.276 1.226 81.6245 18.3755 Settling Bottom TCP3 Sett Bott28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.188 1.953 2.798939 2.04E-07 2.36E-16 0.399788 0.185979 2.91E-08 3.37E-17 1.35E-08 1.57E-17 0.006363 0.188 1.953 91.21906 8.780943 Settling Top TCP3 Sett Top28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.315 10.008 0.809527 9.87E-08 1.14E-16 0.001905 0.146191 2.32E-10 2.69E-19 1.78E-08 2.06E-17 0.003017 0.315 10.01 96.94856 3.051439 Upwelling Bottom TCP3 Up Bott28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.173 1.754 2.867252 1.92E-07 2.22E-16 0.41345 0.187345 2.77E-08 3.2E-17 1.25E-08 1.45E-17 0.006 0.173 1.754 91.02231 8.977686 Upwelling Top TCP 3 Up Top28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0 0.008 0 0 0.125 0 0 0 0 0 0 0.008 100 0 North TCD4N 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 1.606 0.447 26.91215 4.82E-06 5.57E-15 5.22243 0.668243 9.35E-07 1.08E-15 1.2E-07 1.38E-16 0.526813 1.606 0.447 21.77302 78.22698 South TCP4S 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.611 1.754 8.720519 5.94E-07 6.87E-16 1.584104 0.30441 1.08E-07 1.25E-16 2.07E-08 2.4E-17 0.064821 0.611 1.754 74.1649 25.8351 East TCP4 E 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.486 1.262 9.40389 2.04E-06 2.36E-15 1.720778 0.318078 3.73E-07 4.32E-16 6.89E-08 7.98E-17 0.055612 0.486 1.262 72.1968 27.8032 West TCP4W 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.751 2.169 8.68027 2.91E-06 3.36E-15 1.576054 0.303605 5.28E-07 6.11E-16 1.02E-07 1.18E-16 0.079305 0.751 2.169 74.28082 25.71918 Upwelling Top TCP4 Up Top28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.006 0.014 10.16667 2.72E-08 3.15E-17 1.873333 0.333333 5.01E-09 5.8E-18 8.92E-10 1.03E-18 0.000742 0.006 0.014 70 30 Sett Top TCP4 Sett Top28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.072 0.337 5.862469 1.88E-07 2.18E-16 1.012494 0.247249 3.25E-08 3.76E-17 7.94E-09 9.19E-18 0.005128 0.072 0.337 82.39609 17.60391 Upwelling Bottom TCP4 Up Bott28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.697 3.281 5.833808 1.81E-06 2.1E-15 1.006762 0.246676 3.13E-07 3.62E-16 7.67E-08 8.87E-17 0.049398 0.697 3.281 82.47863 17.52137 Sett Bott TCP4 Sett Bott28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.735 0.609 18.73872 6.14E-06 7.11E-15 3.587743 0.504774 1.18E-06 1.36E-15 1.65E-07 1.91E-16 0.16781 0.735 0.609 45.3125 54.6875 Large Square Large Square28.03748 -80.5795 5/14/15 7:18 PM 5/15/2015 13:45 7.947 11.578 13.88252 6.81E-07 7.88E-16 2.616504 0.40765 1.28E-07 1.49E-16 2E-08 2.32E-17 1.343574 7.947 11.58 59.29834 40.70166 Out Of The Mouth TCB1E 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.181 0.058 26.04591 2.48E-07 2.88E-16 5.049182 0.650918 4.82E-08 5.58E-17 6.21E-09 7.19E-18 0.05746 0.181 0.058 24.26778 75.73222 Into The Mouth TCB1W 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.06 0.161 9.176848 2.9E-08 3.36E-17 1.67537 0.313537 5.3E-09 6.13E-18 9.92E-10 1.15E-18 0.006699 0.06 0.161 72.85068 27.14932 Into The Mouth TCB1W 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.055 0.131 10.01732 2.9E-08 3.36E-17 1.843465 0.330346 5.34E-09 6.19E-18 9.58E-10 1.11E-18 0.006705 0.055 0.131 70.43011 29.56989 Into The Mouth TCB1W 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.072 0.167 10.21025 3.88E-08 4.49E-17 1.88205 0.334205 7.14E-09 8.27E-18 1.27E-09 1.47E-18 0.008947 0.072 0.167 69.87448 30.12552 Settling Bottom TCB1SB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.053 0.284 5.210765 5.83E-08 6.74E-17 0.882153 0.234215 9.86E-09 1.14E-17 2.62E-09 3.03E-18 0.003353 0.053 0.284 84.273 15.727 Settling Top TCB1ST 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.016 0.068 6.363757 2.15E-08 2.49E-17 1.112751 0.257275 3.76E-09 4.35E-18 8.68E-10 1E-18 0.001237 0.016 0.068 80.95238 19.04762 Settling Bottom TCB1SB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.015 0.037 9.766026 3.09E-08 3.58E-17 1.793205 0.325321 5.67E-09 6.57E-18 1.03E-09 1.19E-18 0.001783 0.015 0.037 71.15385 28.84615 Settling Top TCB1ST 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.052 0.192 7.149818 7.84E-08 9.08E-17 1.269964 0.272996 1.39E-08 1.61E-17 2.99E-09 3.47E-18 0.00452 0.052 0.192 78.68852 21.31148 Upwelling Bottom TCB1UB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.003 0.017 4.958333 3.14E-09 3.63E-18 0.831667 0.229167 5.26E-10 6.09E-19 1.45E-10 1.68E-19 0.000181 0.003 0.017 85 15 Upwelling Top TCB1UT 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.006 0.002 25.79167 3.26E-08 3.78E-17 4.998333 0.645833 6.33E-09 7.32E-18 8.17E-10 9.46E-19 0.001886 0.006 0.002 25 75 Upwelling Bottom TCB1UB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.003 0.01 7.762821 4.91E-09 5.69E-18 1.392564 0.285256 8.81E-10 1.02E-18 1.81E-10 2.09E-19 0.000283 0.003 0.01 76.92308 23.07692 Upwelling Top TCB1UT 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.001 0.016 1.792484 3.78E-10 4.38E-19 0.198497 0.16585 4.19E-11 4.85E-20 3.5E-11 4.05E-20 2.16E-05 1E-03 0.016 94.11765 5.882353 Out Of The Mouth TCB2E 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.122 0.049 24.52258 1.58E-07 1.83E-16 4.744516 0.620452 3.05E-08 3.53E-17 3.99E-09 4.62E-18 0.036463 0.122 0.049 28.65497 71.34503 Into The Mouth TCB2W 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.024 0.07 8.615248 1.09E-08 1.26E-17 1.56305 0.302305 1.98E-09 2.29E-18 3.83E-10 4.43E-19 0.002515 0.024 0.07 74.46809 25.53191 Into The Mouth TCB2W 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.028 0.097 7.527778 1.11E-08 1.29E-17 1.345556 0.280556 1.99E-09 2.3E-18 4.14E-10 4.8E-19 0.002563 0.028 0.097 77.6 22.4 Into The Mouth TCB2W 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.032 0.088 9.009259 1.52E-08 1.76E-17 1.641852 0.310185 2.77E-09 3.21E-18 5.24E-10 6.06E-19 0.003508 0.032 0.088 73.33333 26.66667 Settling Bottom TCB2SB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.031 0.015 23.14976 1.51E-07 1.75E-16 4.469952 0.592995 2.93E-08 3.39E-17 3.88E-09 4.49E-18 0.008746 0.031 0.015 32.6087 67.3913 Settling Top TCB2ST 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.052 0.013 27.52778 3.02E-07 3.5E-16 5.345556 0.680556 5.87E-08 6.79E-17 7.47E-09 8.65E-18 0.017448 0.052 0.013 20 80 Settling Bottom TCB2SB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.035 0.008 28.01227 2.07E-07 2.4E-16 5.442455 0.690245 4.02E-08 4.65E-17 5.1E-09 5.9E-18 0.011951 0.035 0.008 18.60465 81.39535 Settling Top TCB2ST 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.023 0.004 29.32819 1.42E-07 1.65E-16 5.705638 0.716564 2.77E-08 3.21E-17 3.48E-09 4.03E-18 0.008223 0.023 0.004 14.81481 85.18519 Upwelling Bottom TCB2UB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.007 0.012 12.5424 1.85E-08 2.15E-17 2.34848 0.380848 3.47E-09 4.02E-18 5.63E-10 6.51E-19 0.001069 0.007 0.012 63.15789 36.84211 Upwelling Top TCB2UT 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.002 0.032 1.792484 7.57E-10 8.76E-19 0.198497 0.16585 8.38E-11 9.7E-20 7E-11 8.1E-20 4.31E-05 0.002 0.032 94.11765 5.882353 Upwelling Bottom TCB2UB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.001 0.02 1.403439 2.96E-10 3.43E-19 0.120688 0.158069 2.55E-11 2.95E-20 3.34E-11 3.86E-20 1.68E-05 1E-03 0.02 95.2381 4.761905 Upwelling Top TCB2UT 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 0.006 0.064 2.72619 3.45E-09 4E-18 0.385238 0.184524 4.88E-10 5.65E-19 2.34E-10 2.71E-19 0.000198 0.006 0.064 91.42857 8.571429 Out Of The Mouth TCB3E 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.091 0.022 27.71214 1.33E-07 1.54E-16 5.382429 0.684243 2.59E-08 2.99E-17 3.29E-09 3.81E-18 0.030739 0.091 0.022 19.46903 80.53097 Into The Mouth TCB3W 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.268 0.98 7.206375 1.02E-07 1.18E-16 1.281275 0.274127 1.81E-08 2.1E-17 3.88E-09 4.49E-18 0.023482 0.268 0.98 78.52564 21.47436 Into The Mouth TCB3W 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.035 0.062 12.27864 2.27E-08 2.63E-17 2.295727 0.375573 4.24E-09 4.91E-18 6.94E-10 8.04E-19 0.005232 0.035 0.062 63.91753 36.08247 Into The Mouth TCB3W 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.447 2.096 5.853356 1.38E-07 1.6E-16 1.010671 0.247067 2.39E-08 2.76E-17 5.83E-09 6.75E-18 0.031787 0.447 2.096 82.42234 17.57766 Settling Bottom TCB3SB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.176 1.267 3.985004 1.48E-07 1.72E-16 0.637001 0.2097 2.37E-08 2.74E-17 7.8E-09 9.03E-18 0.008504 0.176 1.267 87.80319 12.19681 Settling Top TCB3ST 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.042 0.099 10.09279 8.96E-08 1.04E-16 1.858558 0.331856 1.65E-08 1.91E-17 2.95E-09 3.41E-18 0.005159 0.042 0.099 70.21277 29.78723 Settling Bottom TCB3SB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.118 1.208 2.839911 7.08E-08 8.2E-17 0.407982 0.186798 1.02E-08 1.18E-17 4.66E-09 5.39E-18 0.004053 0.118 1.208 91.10106 8.898944 Settling Top TCB3ST 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.029 0.016 22.12654 1.36E-07 1.57E-16 4.265309 0.572531 2.61E-08 3.03E-17 3.51E-09 4.06E-18 0.00782 0.029 0.016 35.55556 64.44444 Upwelling Bottom TCB3UB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.028 0.068 9.877315 5.85E-08 6.77E-17 1.815463 0.327546 1.07E-08 1.24E-17 1.94E-09 2.24E-18 0.003366 0.028 0.068 70.83333 29.16667 Upwelling Top TCB3UT 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.034 0.009 27.20478 1.96E-07 2.26E-16 5.280956 0.674096 3.8E-08 4.39E-17 4.84E-09 5.61E-18 0.011274 0.034 0.009 20.93023 79.06977 Upwelling Bottom TCB3UB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.023 0.01 23.95034 1.16E-07 1.35E-16 4.630067 0.609007 2.25E-08 2.61E-17 2.96E-09 3.43E-18 0.006714 0.023 0.01 30.30303 69.69697 Upwelling Top TCB3UT 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.003 0.035 2.491228 1.58E-09 1.83E-18 0.338246 0.179825 2.14E-10 2.48E-19 1.14E-10 1.32E-19 9.03E-05 0.003 0.035 92.10526 7.894737

4-47

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute of

Technology Final Report, July 2016

Appendix I – continued

Conv ersio Conversi Conversi Conversi Conversi Conversi n of on of on of on of on of on of Conversion of Conversion of Conversion of Conversion Conversion of Inorg Dry Weight Organic Organic Organic Organic Inorganic Inorganic inorganic inorganic inorganic Organic Dry Weight Dry Weight Dry Weight of Organic Organic anic Longitud Flux Over Weight Flux Weight Flux Weight Weight Weight Flux Weight Flux Weight Weight Weight Weight Name stb Lattitutde Date Time In Date Time Out Flux Over Flux Over Flux Over Weight Flux Weight Flux Weig e Sonde Over Sonde Over Sonde Flux Over Flux Over Over Sonde Over Sonde Flux Over Flux Over Flux Over lbs/(yr Sonde g/(m2 Sonde kg/(m2 Sonde lbs/(m2 Over Sonde Over Sonde ht g/(cm2 s) g/(cm2 min) g/(cm2 s) Sonde Sonde g/(cm2 min) g/(cm2 s) Sonde Sonde Sonde m^3) day) yr) yr) g/(m2 min) g/(m2 day) Flux kg/(m2 lbs/(m2 g/(m2 kg/(m2 lbs/(m2 Over yr) yr) day) yr) yr) Sond e Out Of The Mouth TC1E 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.00055641 133.53951352 48.74192243 107.45754474 0.00000370 0.00022172 0.03695334 53.21281375 19.423 42.820 0.00000558 0.00033469 0.056 80.327 29.319 64.638 10.48514 Into The Mouth TC1W 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.00044344 106.42562750 38.84535404 85.63934619 0.00000169 0.00010150 0.01691597 24.35899921 8.891 19.601 0.00000570 0.00034194 0.057 82.067 29.954 66.038 8.356237 Settling Bottom TC1SB 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.00041580 99.79159721 36.42393298 80.30102656 0.00000218 0.00013054 0.02175689 31.32992005 11.435 25.211 0.00000475 0.00028526 0.048 68.462 24.989 55.090 31.38459 Settling Top TC1ST 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.00018614 44.67414526 16.30606302 35.94871538 0.00000109 0.00006527 0.01087844 15.66496003 5.718 12.605 0.00000201 0.00012087 0.020 29.009 10.588 23.343 14.05008 Upwelling Bottom TC1UB 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.00397909 954.98237793 348.56856794 768.46214951 0.00006531 0.00391866 0.65310957 940.47778531 343.274 756.790 0.00000101 0.00006044 0.010 14.505 5.294 11.672 300.3432 Upwelling Top TC1UT 28.037996 -80.5788 3/5/15 1:45 PM 3/6/15 10:10 AM 0.00402986 967.16623572 353.01567604 778.26634461 0.00000149 0.00008944 0.01490750 21.46679707 7.835 17.274 0.00006567 0.00394041 0.657 945.699 345.180 760.992 304.1751 Out Of The Mouth TC2E 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.00068268 163.84326849 59.80279300 131.84259018 0.00000344 0.00020662 0.03443609 49.58796268 18.100 39.903 0.00000793 0.00047606 0.079 114.255 41.703 91.940 12.86451 Into The Mouth TC2W 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.00090319 216.76609415 79.11962436 174.42891356 0.00000389 0.00023320 0.03886646 55.96770056 20.428 45.036 0.00001117 0.00066999 0.112 160.798 58.691 129.392 17.01986 Settling Bottom TC2SB 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.00051491 123.57912910 45.10638212 99.44255033 0.00000290 0.00017406 0.02900919 41.77322674 15.247 33.614 0.00000568 0.00034086 0.057 81.806 29.859 65.828 38.8658 Settling Top TC2ST 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.00027800 66.72112604 24.35321100 53.68963985 0.00000145 0.00008703 0.01450459 20.88661337 7.624 16.807 0.00000318 0.00019098 0.032 45.835 16.730 36.882 20.98388 Upwelling Bottom TC2UB 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.00010878 26.10826671 9.52951735 21.00898951 0.00000149 0.00008944 0.01490750 21.46679707 7.835 17.274 0.00000032 0.00001934 0.003 4.641 1.694 3.735 8.211085 Upwelling Top TC2UT 28.038338 -80.5788 3/5/15 2:20 PM 3/6/15 10:45 AM 0.00003626 8.70275557 3.17650578 7.00299650 0.00000060 0.00003626 0.00604358 8.70275557 3.177 7.003 0.00000000 0.00000000 0.000 0.000 0.000 0.000 2.737028 Out Of The Mouth TC3E 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.00061342 147.22127099 53.73576391 118.46708062 0.00000248 0.00014878 0.02479629 35.70665155 13.033 28.733 0.00000774 0.00046464 0.077 111.515 40.703 89.734 11.5594 Into The Mouth TC3W 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.00071528 171.66659397 62.65830680 138.13792050 0.00000352 0.00021134 0.03522344 50.72175630 18.513 40.815 0.00000840 0.00050394 0.084 120.945 44.145 97.323 13.47877 Settling Bottom TC3SB 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.00045184 108.44052130 39.58079027 87.26070556 0.00000193 0.00011601 0.01933530 27.84283655 10.163 22.405 0.00000560 0.00033582 0.056 80.598 29.418 64.856 34.10469 Settling Top TC3ST 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.00016639 39.93248926 14.57535858 32.13316522 0.00000069 0.00004121 0.00686912 9.89153404 3.610 7.960 0.00000209 0.00012517 0.021 30.041 10.965 24.174 12.55882 Upwelling Bottom TC3UB 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.00005343 12.82235894 4.68016101 10.31798883 0.00000036 0.00002137 0.00356177 5.12894358 1.872 4.127 0.00000053 0.00003206 0.005 7.693 2.808 6.191 4.032649 Upwelling Top TC3UT 28.038671 -80.579 3/5/15 2:45 PM 3/6/15 11:05 PM 0.00008090 19.41671496 7.08710096 15.62438309 0.00000051 0.00003053 0.00508824 7.32706225 2.674 5.896 0.00000084 0.00005037 0.008 12.090 4.413 9.728 6.106583 Out Of The Mouth TC4E 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.00102560 246.14518719 89.84299332 198.06989533 0.00000658 0.00039455 0.06575870 94.69252420 34.563 76.198 0.00001052 0.00063105 0.105 151.453 55.280 121.872 19.32662 Into The Mouth TC4W 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.00081795 196.30701655 71.65206104 157.96575454 0.00000383 0.00022958 0.03826310 55.09886642 20.111 44.337 0.00000981 0.00058837 0.098 141.208 51.541 113.628 15.41347 Settling Bottom TC4SB 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.00153030 367.27256458 134.05448607 295.53955231 0.00000773 0.00046394 0.07732297 111.34507614 40.641 89.598 0.00001777 0.00106636 0.178 255.927 93.414 205.942 115.5077 Settling Top TC4ST 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.00016157 38.77689219 14.15356565 31.20327098 0.00000165 0.00009925 0.01654173 23.82009092 8.694 19.168 0.00000104 0.00006232 0.010 14.957 5.459 12.036 12.19538 Upwelling Bottom TC4UB 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.00007386 17.72657929 6.47020144 14.26435245 0.00000119 0.00007155 0.01192543 17.17262368 6.268 13.819 0.00000004 0.00000231 0.000 0.554 0.202 0.446 5.575033 Upwelling Top TC4UT 28.038813 -80.5793 3/5/15 2:07 PM 3/6/15 11:30 AM 0.00006694 16.06471248 5.86362005 12.92706941 0.00000092 0.00005540 0.00923259 13.29493446 4.853 10.698 0.00000019 0.00001154 0.002 2.770 1.011 2.229 5.052373 Out Of The Mouth TC5E 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.00136307 327.13686693 119.40495643 263.24286789 0.00000094 0.00005642 0.00940258 13.53971011 4.942 10.895 0.00002178 0.00130665 0.218 313.597 114.463 252.348 25.68586 Into The Mouth TC5W 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.00109252 262.20449370 95.70464020 210.99261463 0.00000493 0.00029603 0.04933825 71.04708103 25.932 57.171 0.00001327 0.00079649 0.133 191.157 69.772 153.822 20.58755 Settling Bottom TC5SB 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.00074519 178.84638258 65.27892964 143.91540489 0.00000279 0.00016749 0.02791441 40.19674397 14.672 32.346 0.00000963 0.00057771 0.096 138.650 50.607 111.570 56.24743 Settling Top TC5ST 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.00062625 150.30086874 54.85981709 120.94519369 0.00000166 0.00009952 0.01658682 23.88502178 8.718 19.220 0.00000878 0.00052673 0.088 126.416 46.142 101.725 47.26982 Upwelling Bottom TC5UB 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.00012622 30.29319835 11.05701740 24.37655067 0.00000093 0.00005583 0.00930480 13.39891466 4.891 10.782 0.00000117 0.00007039 0.012 16.894 6.166 13.595 9.527251 Upwelling Top TC5UT 28.039262 -80.5793 3/5/15 3:25 PM 3/6/15 11:45 AM 0.00015050 36.11881342 13.18336690 29.06434887 0.00000101 0.00006068 0.01011392 14.56403767 5.316 11.719 0.00000150 0.00008981 0.015 21.555 7.867 17.345 11.35941 Out Of The Mouth TC6E 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.00076648 183.95592764 67.14391359 148.02699069 0.00000251 0.00015047 0.02507857 36.11314285 13.181 29.060 0.00001027 0.00061601 0.103 147.843 53.963 118.967 14.4437 Into The Mouth TC6W 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.00081255 195.01097136 71.17900455 156.92284349 0.00000271 0.00016275 0.02712580 39.06115451 14.257 31.432 0.00001083 0.00064979 0.108 155.950 56.922 125.491 15.31171 Settling Bottom TC6SB 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.00052592 126.22004829 46.07031762 101.56766435 0.00000291 0.00017449 0.02908107 41.87674499 15.285 33.698 0.00000586 0.00035143 0.059 84.343 30.785 67.870 39.69637 Settling Top TC6ST 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.00025559 61.34058421 22.38931324 49.35998641 0.00000168 0.00010076 0.01679330 24.18234570 8.827 19.459 0.00000258 0.00015483 0.026 37.158 13.563 29.901 19.2917 Upwelling Bottom TC6UB 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.00026787 64.28965076 23.46572253 51.73306268 0.00000143 0.00008601 0.01433574 20.64346584 7.535 16.612 0.00000303 0.00018186 0.030 43.646 15.931 35.122 20.21918 Upwelling Top TC6UT 28.03976 -80.5793 3/5/15 3:55 PM 3/6/15 12:00 PM 0.00016466 39.51749175 14.42388449 31.79922201 0.00000098 0.00005898 0.00983022 14.15551943 5.167 11.391 0.00000176 0.00010567 0.018 25.362 9.257 20.408 12.4283 North TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00147224 353.33851705 128.96855872 284.32700183 0.00000244 0.00014658 0.02442962 35.17865177 12.840 28.308 0.00002209 0.00132567 0.221 318.160 116.128 256.019 27.74313 South TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00080330 192.79280725 70.36937465 155.13791510 0.00000172 0.00010347 0.01724444 24.83198948 9.064 19.982 0.00001166 0.00069984 0.117 167.961 61.306 135.156 15.13754 Out Of The Mouth TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00086581 207.79546756 75.84534566 167.21036467 0.00000333 0.00019975 0.03329134 47.93953526 17.498 38.576 0.00001110 0.00066607 0.111 159.856 58.347 128.634 16.31551 Into The Mouth TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00123729 296.94920759 108.38646077 238.95124312 0.00000249 0.00014945 0.02490863 35.86842926 13.092 28.863 0.00001813 0.00108784 0.181 261.081 95.294 210.088 23.31561 Settling Bottom TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00279747 671.39365264 245.05868321 540.26191624 0.00000570 0.00034214 0.05702284 82.11289277 29.971 66.075 0.00004092 0.00245534 0.409 589.281 215.087 474.187 211.1542 Settling Top TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00038526 92.46325740 33.74908895 74.40400491 0.00000077 0.00004600 0.00766694 11.04038894 4.030 8.884 0.00000565 0.00033926 0.057 81.423 29.719 65.520 29.07982 Upwelling Bottom TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00256459 615.50168361 224.65811452 495.28636104 0.00000043 0.00002588 0.00431265 6.21021878 2.267 4.997 0.00004231 0.00253871 0.423 609.291 222.391 490.289 193.5761 Upwelling Top TCOUT1N28.040005 -80.5783 4/10/2015 16:40 4/11/2015 9:50 0.00013800 33.12116683 12.08922589 26.65218086 0.00000177 0.00010638 0.01772979 25.53089943 9.319 20.544 0.00000053 0.00003163 0.005 7.590 2.770 6.108 10.41665 North TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00107509 258.02220402 94.17810447 207.62717942 0.00000280 0.00016823 0.02803857 40.37553629 14.737 32.490 0.00001511 0.00090686 0.151 217.647 79.441 175.137 20.25917 South TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00105054 252.13049486 92.02763062 202.88619614 0.00000197 0.00011841 0.01973530 28.41883241 10.373 22.868 0.00001554 0.00093213 0.155 223.712 81.655 180.018 19.79657 Out Of The Mouth TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00103249 247.79835577 90.44639986 199.40017902 0.00000235 0.00014079 0.02346575 33.79068488 12.334 27.191 0.00001486 0.00089170 0.149 214.008 78.113 172.209 19.45642 Into The Mouth TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00092636 222.32537794 81.14876295 178.90239838 0.00000208 0.00012491 0.02081834 29.97840248 10.942 24.123 0.00001336 0.00080145 0.134 192.347 70.207 154.779 17.45636 Settling Bottom TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00125388 300.93138205 109.83995445 242.15564816 0.00000188 0.00011268 0.01877932 27.04222097 9.870 21.761 0.00001902 0.00114120 0.190 273.889 99.970 220.395 94.64332 Settling Top TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00058938 141.45161737 51.62984034 113.82431388 0.00000404 0.00024269 0.04044777 58.24478362 21.259 46.869 0.00000578 0.00034670 0.058 83.207 30.370 66.955 44.48672 Upwelling Bottom TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00006645 15.94797647 5.82101141 12.83313343 0.00000034 0.00002022 0.00337065 4.85373197 1.772 3.906 0.00000077 0.00004623 0.008 11.094 4.049 8.927 5.01566 Upwelling Top TCOUT1S28.038344 -80.5774 4/10/2015 17:10 4/11/2015 10:15 0.00014157 33.97612378 12.40128518 27.34015382 0.00000164 0.00009823 0.01637171 23.57526956 8.605 18.971 0.00000072 0.00004334 0.007 10.401 3.796 8.369 10.68554 Out Of The Mouth TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.00035915 86.19682624 31.46184158 69.36148761 0.00000140 0.00008417 0.01402754 20.19966029 7.373 16.254 0.00000458 0.00027499 0.046 65.997 24.089 53.107 6.767929 Into The Mouth TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.00030619 73.48497106 26.82201444 59.13241974 0.00000079 0.00004716 0.00786026 11.31877516 4.131 9.108 0.00000432 0.00025903 0.043 62.166 22.691 50.024 5.769831 Settling Bottom TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.00082163 197.19135865 71.97484591 158.67737336 0.00000363 0.00021775 0.03629111 52.25919399 19.075 42.052 0.00001006 0.00060388 0.101 144.932 52.900 116.625 15.4829 Settling Top TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.00030775 73.85966084 26.95877621 59.43392783 0.00000044 0.00002613 0.00435493 6.27110328 2.289 5.046 0.00000469 0.00028162 0.047 67.589 24.670 54.388 5.79925 Upwelling Bottom TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.00081292 195.10099089 71.21186168 156.99528106 0.00000155 0.00009291 0.01548421 22.29725610 8.138 17.942 0.00001200 0.00072002 0.120 172.804 63.073 139.053 61.35952 Upwelling Top TCB1 28.032076 -80.5825 4/10/2015 14:30 4/11/2015 7:30 0.00002613 6.27110328 2.28895270 5.04627689 0.00000227 0.00013645 0.02274243 32.74909490 11.953 26.353 -0.00000184 -0.00011032 -0.018 -26.478 -9.664 -21.307 1.97227 Out Of The Mouth TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.00023073 55.37493080 20.21184974 44.55950113 0.00000057 0.00003410 0.00568357 8.18434512 2.987 6.586 0.00000328 0.00019663 0.033 47.191 17.225 37.974 4.347882 Into The Mouth TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.00036713 88.11231127 32.16099361 70.90285400 0.00000156 0.00009360 0.01559959 22.46341532 8.199 18.076 0.00000456 0.00027354 0.046 65.649 23.962 52.827 6.918328 Settling Bottom TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.00021775 52.25919399 19.07460581 42.05230743 0.00000198 0.00011903 0.01983914 28.56835938 10.427 22.989 0.00000165 0.00009871 0.016 23.691 8.647 19.064 4.103243 Settling Top TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.00042388 101.73123096 37.13189930 81.86182513 0.00000474 0.00028452 0.04742038 68.28534681 24.924 54.948 0.00000232 0.00013936 0.023 33.446 12.208 26.913 7.987647 Upwelling Bottom TCB2 28.03168 -80.5823 4/10/2015 14:50 4/11/2015 7:50 0.00021194 50.86561548 18.56594965 40.93091256 0.00000285 0.00017129 0.02854900 41.11056594 15.005 33.081 0.00000068 0.00004065 0.007 9.755 3.561 7.850 15.9973 Out Of The Mouth TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 0.00386427 927.42433573 338.50988254 746.28654415 0.00006090 0.00365416 0.60902655 876.99823676 320.104 705.709 0.00000350 0.00021011 0.035 50.426 18.406 40.577 72.81872 Into The Mouth TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 0.00036968 88.72220850 32.38360610 71.39363053 0.00000164 0.00009820 0.01636586 23.56683663 8.602 18.964 0.00000452 0.00027148 0.045 65.155 23.782 52.430 6.966215 Settling Bottom TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 0.00532755 1278.61167857 466.69326268 1028.88252350 0.00005157 0.00309425 0.51570902 742.62099119 271.057 597.578 0.00003722 0.00223329 0.372 535.991 195.637 431.305 100.3929 Settling Top TCB3 28.031876 -0.58253 4/10/2015 15:15 4/11/2015 8:20 0.00101119 242.68659843 88.58060843 195.28681303 0.00000154 0.00009245 0.01540867 22.18848900 8.099 17.855 0.00001531 0.00091874 0.153 220.498 80.482 177.432 19.05506 Upwelling Top TCB3 28.036151 -80.5797 4/10/2015 15:15 4/11/2015 8:20 0.00001733 4.16034169 1.51852472 3.34777394 0.00000000 0.00000000 0.00000000 0.00000000 0.000 0.000 0.00000029 0.00001733 0.003 4.160 1.519 3.348 1.308433 Into The Mouth TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.00295132 708.31786841 258.53602197 569.97436212 0.00000977 0.00058608 0.09767977 140.65886749 51.340 113.186 0.00003942 0.00236525 0.394 567.659 207.196 456.788 55.6151 Settling Bottom TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.00105928 254.22655003 92.79269076 204.57286503 0.00000478 0.00028706 0.04784315 68.89413918 25.146 55.438 0.00001287 0.00077222 0.129 185.332 67.646 149.135 19.96115 Settling Top TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.00062517 150.04195252 54.76531267 120.73684710 0.00000264 0.00015854 0.02642286 38.04891619 13.888 30.617 0.00000778 0.00046664 0.078 111.993 40.877 90.119 11.78087 Upwelling Bottom TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.00087345 209.62799108 76.51421674 168.68497299 0.00000603 0.00036194 0.06032388 86.86639356 31.706 69.900 0.00000853 0.00051151 0.085 122.762 44.808 98.785 65.92828 Upwelling Top TCB4 28.036151 -80.5797 4/10/2015 4/11/2015 8:50 0.00298828 717.18617496 261.77295386 577.11057539 0.00004736 0.00284170 0.47361727 682.00887509 248.933 548.804 0.00000244 0.00014657 0.024 35.177 12.840 28.307 225.556 Out Of The Mouth TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.00052058 124.9388913 45.60269531 100.5367336 1.87726E-06 0.00011264 0.018772603 27.0325479 9.86688 21.75275 6.79905E-06 0.00040794 0.068 97.90634 35.73582 78.78399 9.809846 Into The Mouth TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.00194730 467.3511647 170.5831751 376.0715265 3.41758E-06 0.00020505 0.034175764 49.21310003 17.96278 39.60115 2.90374E-05 0.00174224 0.29 418.1381 152.6204 336.4704 36.69508 Settling Bottom TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.00124521 298.8512112 109.0806921 240.4817612 2.02239E-06 0.00012134 0.020223883 29.12239181 10.62967 23.43442 1.87312E-05 0.00112387 0.187 269.7288 98.45102 217.0473 23.46495 Settling Top TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.00032069 76.96632122 28.09270724 61.93381785 2.60021E-06 0.00015601 0.026002136 37.44307519 13.66672 30.12997 2.74467E-06 0.00016468 0.027 39.52325 14.42598 31.80385 6.043176 Upwelling Bottom TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.00120188 288.450357 105.2843803 232.1123263 3.46695E-06 0.00020802 0.034669514 49.92410025 18.2223 40.17329 1.65643E-05 0.00099386 0.166 238.5263 87.06208 191.939 90.71802 Upwelling Top TCB6 28.037183 -80.5796 4/10/2015 16:00 4/11/2015 9:05 0.00434813 1043.552373 380.8966162 839.733296 3.84254E-05 0.00230552 0.384253781 553.3254444 201.9638 445.2539 3.40435E-05 0.00204261 0.34 490.2269 178.9328 394.4794 328.1986 Out Of The Mouth TCB7 28.038323 -80.5797 4/10/2015 15:40 4/11/2015 9:30 0.00227210 545.3029467 199.0355755 438.798332 6.05201E-06 0.00036312 0.060520051 87.14887275 31.80934 70.12759 3.18163E-05 0.00190898 0.318 458.1541 167.2262 368.6707 42.81564 Into The Mouth TCB7 28.038323 -80.5797 4/10/2015 15:40 4/11/2015 9:30 0.00178102 427.4444711 156.017232 343.9591187 5.00299E-06 0.00030018 0.050029908 72.04306814 26.29572 57.97214 2.46807E-05 0.00148084 0.247 355.4014 129.7215 285.987 33.56172 Upwelling Top TCB7 28.038323 -80.5797 4/10/2015 15:40 4/11/2015 9:30 0.00004081 9.793873319 3.574763761 7.88100505 1.72914E-07 0.00001037 0.001729144 2.489967793 0.908838 2.003645 5.07216E-07 0.00003043 0.005 7.303906 2.665926 5.87736

4-48

Impacts of Environmental Muck Dredging 2014-2015 at Florida Institute of

Technology Final Report, July 2016

Appendix I – continued

Conv ersio Conversi Conversi Conversi Conversi Conversi n of on of on of on of on of on of Conversion of Conversion of Conversion of Conversion Conversion of Inorg Dry Weight Organic Organic Organic Organic Inorganic Inorganic inorganic inorganic inorganic Organic Dry Weight Dry Weight Dry Weight of Organic Organic anic Longitud Flux Over Weight Flux Weight Flux Weight Weight Weight Flux Weight Flux Weight Weight Weight Weight Name stb Lattitutde Date Time In Date Time Out Flux Over Flux Over Flux Over Weight Flux Weight Flux Weig e Sonde Over Sonde Over Sonde Flux Over Flux Over Over Sonde Over Sonde Flux Over Flux Over Flux Over lbs/(yr Sonde g/(m2 Sonde kg/(m2 Sonde lbs/(m2 Over Sonde Over Sonde ht g/(cm2 s) g/(cm2 min) g/(cm2 s) Sonde Sonde g/(cm2 min) g/(cm2 s) Sonde Sonde Sonde m^3) day) yr) yr) g/(m2 min) g/(m2 day) Flux kg/(m2 lbs/(m2 g/(m2 kg/(m2 lbs/(m2 Over yr) yr) day) yr) yr) Sond e Out Of The Mouth TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.00145704 349.6902671 127.6369475 281.3913016 3.94706E-06 0.00023682 0.039470601 56.83766482 20.74575 45.73654 2.0337E-05 0.00122022 0.203 292.8526 106.8912 235.6548 27.45668 Into The Mouth TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.00285055 684.1314046 249.7079627 550.5118229 9.43444E-06 0.00056607 0.094344362 135.8558818 49.5874 109.3215 3.80747E-05 0.00228448 0.381 548.2755 200.1206 441.1903 53.71605 Settling Bottom TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.00239509 574.8205431 209.8094982 462.5507657 4.09293E-06 0.00024558 0.040929287 58.9381739 21.51243 47.4268 3.58252E-05 0.00214951 0.358 515.8824 188.2971 415.124 45.13327 Settling Top TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.00030625 73.49936981 26.82726998 59.14400623 4.33369E-07 0.00002600 0.004333689 6.240512531 2.277787 5.021661 4.67075E-06 0.00028025 0.047 67.25886 24.54948 54.12235 5.770961 Upwelling Bottom TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.04943006 11863.21432 4330.073227 9546.177383 1.04972E-05 0.00062983 0.104971584 151.1590813 55.17306 121.6358 0.000813337 0.04880023 8.133 11712.06 4274.9 9424.542 3730.997 Upwelling Top TC4 28.038813 -80.5793 4/10/2015 16:00 4/11/2015 9:05 0.00175370 420.8879007 153.6240838 338.68313 2.88913E-06 0.00017335 0.028891262 41.60341687 15.18525 33.47774 2.63392E-05 0.00158035 0.263 379.2845 138.4388 305.2054 North + TCB5N 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00374360 898.4648047 327.9396537 722.9831786 5.96043E-05 0.00357626 0.596043369 858.3024514 313.2804 690.665 2.78905E-06 0.00016734 0.028 40.16235 14.65926 32.31813 70.5449 South- TCB5S 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00070396 168.950447 61.66691315 135.9522716 3.26378E-06 0.00019583 0.032637846 46.99849862 17.15445 37.81909 8.46889E-06 0.00050813 0.085 121.9519 44.51246 98.13318 13.26551 East + TCB5E 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00190707 457.6971552 167.0594617 368.303068 5.56314E-06 0.00033379 0.055631399 80.10921393 29.23986 64.46286 2.62214E-05 0.00157328 0.262 377.5879 137.8196 303.8402 35.93708 West - TCB5W 28.037894 -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00468321 1123.971349 410.2495424 904.4454211 1.86908E-05 0.00112145 0.186907931 269.14742 98.23881 216.5795 5.93628E-05 0.00356177 0.594 854.8239 312.0107 687.8659 88.25103 Settling Bottom TCB5 Sett28.037894 Bott -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00305091 732.2177542 267.2594803 589.2062956 8.00549E-06 0.00048033 0.080054939 115.2791127 42.07688 92.76363 4.2843E-05 0.00257058 0.428 616.9386 225.1826 496.4427 230.2835 Settling Top TCB 5 Sett28.037894 Top -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00472392 1133.740765 413.8153794 912.3067459 1.15333E-06 0.00006920 0.011533339 16.60800777 6.061923 13.36425 7.75787E-05 0.00465472 0.776 1117.133 407.7535 898.9425 356.563 Upwelling Bottom TCB 5Up 28.037894Bott -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00024220 58.12802718 21.21672992 46.77488271 7.12353E-07 0.00004274 0.007123533 10.25788715 3.744129 8.254391 3.32432E-06 0.00019946 0.033 47.87014 17.4726 38.52049 18.28134 Upwelling Top TCB5 Up 28.037894Top -80.5801 5/14/15 4:45 PM 5/15/2015 17:00 0.00005088 12.21177042 4.457296202 9.826656031 0 0.00000000 0 0 0 0 8.4804E-07 0.00005088 0.008 12.21177 4.457296 9.826656 3.840618 North TCP1 N 28.038801 -80.5803 5/14/15 5:20 PM 5/15/2015 15:45 0.00398209 955.7020918 348.8312635 769.0412941 5.54001E-05 0.00332400 0.554000692 797.7609972 291.1828 641.9481 1.09681E-05 0.00065809 0.11 157.9411 57.6485 127.0932 75.03901 South TCP1S 28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.01042981 2503.155057 913.6515959 2014.256975 9.17068E-06 0.00055024 0.091706786 132.0577714 48.20109 106.2652 0.00016466 0.00987957 1.647 2371.097 865.4505 1907.992 196.5406 East TCP1 E 28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.02030234 4872.561768 1778.485045 3920.88836 0.000124729 0.00748375 1.247291618 1796.099929 655.5765 1445.299 0.000213643 0.01281859 2.136 3076.462 1122.909 2475.59 382.5797 West TCP1W 28.038801 -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.00964587 2315.00847 844.9780917 1862.857814 4.1136E-05 0.00246816 0.411360372 592.3589352 216.211 476.6637 0.000119628 0.00717771 1.196 1722.65 628.7671 1386.194 181.7679 Settling Top TCP1 Sett28.038801 Top -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.00068474 164.338652 59.98360797 132.241219 1.54123E-06 0.00009247 0.015412253 22.19364432 8.10068 17.85894 9.87118E-06 0.00059227 0.099 142.145 51.88293 114.3823 51.68473 Settling Bottom TCP1 Sett28.038801 Bott -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.01287584 3090.200761 1127.923278 2486.645172 3.72463E-05 0.00223478 0.372462781 536.3464043 195.7664 431.5911 0.000177351 0.01064106 1.774 2553.854 932.1568 2055.054 971.8723 Upwelling Bottom TCP1 Up 28.038801Bott -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.00018495 44.38728863 16.20136035 35.71788551 6.23829E-07 0.00003743 0.006238293 8.983141747 3.278847 7.22862 2.45862E-06 0.00014752 0.025 35.40415 12.92251 28.48927 13.95986 Upwelling Top TCP1 Up 28.038801Top -80.5803 5/14/15 5:20 PM 5/15/15 3:45 PM 0.00008146 19.5515438 7.136313488 15.73287814 3.66958E-07 0.00002202 0.003669584 5.284201028 1.928733 4.252129 9.90788E-07 0.00005945 0.01 14.26734 5.20758 11.48075 6.148987 North TCP2N 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.00118928 285.4275174 104.1810438 229.6798858 1.39792E-05 0.00083875 0.13979171 201.3000629 73.47452 161.9836 5.84218E-06 0.00035053 0.058 84.12745 30.70652 67.69629 22.41096 South TCP2S 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.00333894 801.3449837 292.490919 644.8320963 1.178E-05 0.00070680 0.117799854 169.6317904 61.9156 136.5005 4.3869E-05 0.00263214 0.439 631.7132 230.5753 508.3316 62.91933 Settling Top TCP2E 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.00322535 774.0842471 282.5407502 622.8957289 1.13251E-05 0.00067950 0.11325076 163.081094 59.5246 131.2293 4.24308E-05 0.00254585 0.424 611.0032 223.0162 491.6665 60.77889 West TCP2W 28.038189 -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.00198571 476.5714404 173.9485757 383.4909648 3.29422E-05 0.00197653 0.329421973 474.3676418 173.1442 381.7176 1.53042E-07 0.00000918 0.002 2.203799 0.804386 1.773369 37.41903 Settling Bottom TCP2 Sett28.038189 Bott -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.03088302 7411.925535 2705.35282 5964.282022 3.4817E-06 0.00020890 0.034816957 50.13641743 18.29979 40.34414 0.000511235 0.03067412 5.112 7361.789 2687.053 5923.938 2331.06 Settling Top TCP2 Sett28.038189 Top -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.00034664 83.19339595 30.36558952 66.94466553 8.41729E-07 0.00005050 0.008417286 12.12089213 4.424126 9.753527 4.93559E-06 0.00029614 0.049 71.0725 25.94146 57.19114 26.16443 Upwelling Down TCP2 Up 28.038189Down -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.00037648 90.3557413 32.97984557 72.70811356 7.65208E-08 0.00000459 0.000765208 1.101899284 0.402193 0.886684 6.19818E-06 0.00037189 0.062 89.25384 32.57765 71.82143 28.417 Upwelling Top TCP2 Up 28.038189Top -80.5813 5/14/2015 17:40 5/15/2015 15:10 0.00119602 287.0447635 104.7713387 230.9812632 1.62607E-05 0.00097564 0.162606665 234.1535979 85.46606 188.4204 3.673E-06 0.00022038 0.037 52.89117 19.30528 42.56085 90.27596 North TCP3N 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.00054214 130.1136739 47.49149097 104.7008152 7.39106E-06 0.00044346 0.073910634 106.4313135 38.84743 85.64392 1.64461E-06 0.00009868 0.016 23.68236 8.644062 19.05689 10.21616 South TCP3S 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.00132865 318.8760166 116.3897461 256.5954669 6.77192E-08 0.00000406 0.000677192 0.975156014 0.355932 0.784696 2.20764E-05 0.00132459 0.221 317.9009 116.0338 255.8108 25.03724 East TCP3E 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.00273606 656.6541922 239.6787802 528.4012603 7.93566E-06 0.00047614 0.079356554 114.2734375 41.7098 91.95438 3.76653E-05 0.00225992 0.377 542.3808 197.969 436.4469 51.55862 West TCP3W 28.036987 -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.00348859 837.2619666 305.6006178 673.7340347 1.06841E-05 0.00064105 0.106841019 153.8510671 56.15564 123.802 4.74591E-05 0.00284755 0.475 683.4109 249.445 549.932 65.73943 Settling Bottom TCP3 Sett28.036987 Bott -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.00497275 1193.460633 435.613131 960.3625622 7.27758E-06 0.00043665 0.072775766 104.7971037 38.25094 84.32889 7.56016E-05 0.00453610 0.756 1088.664 397.3622 876.0337 375.345 Settling Top TCP3 Sett28.036987 Top -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.02397652 5754.364369 2100.342995 4630.463675 1.21938E-05 0.00073163 0.121938119 175.5908918 64.09068 141.2958 0.000387415 0.02324489 3.874 5578.773 2036.252 4489.168 1809.755 Upwelling Bottom TCP3 Up 28.036987Bott -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.00447571 1074.170313 392.0721641 864.3711617 6.69692E-06 0.00040182 0.066969189 96.43563264 35.19901 77.60052 6.78982E-05 0.00407389 0.679 977.7347 356.8732 786.7706 337.828 Upwelling Top TCP 3 Up28.036987 Top -80.5812 5/14/2015 17:15 5/15/2015 14:30 0.00001858 4.45945122 1.627699695 3.588463567 0 0.00000000 0 0 0 0 3.09684E-07 0.00001858 0.003 4.459451 1.6277 3.588464 1.402503 North TCD4N 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.00137251 329.4030202 120.2321024 265.0664125 1.78946E-05 0.00107368 0.178945869 257.6820509 94.05395 207.3535 4.98062E-06 0.00029884 0.05 71.72097 26.17815 57.71295 25.86379 South TCP4S 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.00158110 379.4632941 138.5041023 305.349277 6.80797E-06 0.00040848 0.068079655 98.03470304 35.78267 78.88728 1.95437E-05 0.00117262 0.195 281.4286 102.7214 226.462 29.79438 East TCP4 E 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.00467610 1122.265011 409.6267289 903.0723523 2.16684E-05 0.00130011 0.216684463 312.0256266 113.8894 251.083 5.62666E-05 0.00337600 0.563 810.2394 295.7374 651.9893 88.11705 West TCP4W 28.035898 -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.00781134 1874.721871 684.2734831 1508.564799 3.34835E-05 0.00200901 0.334835456 482.1630567 175.9895 387.9905 9.67055E-05 0.00580233 0.967 1392.559 508.284 1120.574 147.1978 Upwelling Top TCP4 Up 28.035898Top -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.00005350 12.84056076 4.686804679 10.33263561 2.67512E-07 0.00001605 0.002675117 3.852168229 1.406041 3.099791 6.24194E-07 0.00003745 0.006 8.988393 3.280763 7.232845 4.038373 Sett Top TCP4 Sett28.035898 Top -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.00109412 262.5894676 95.84515568 211.3023982 3.21014E-06 0.00019261 0.032101402 46.22601875 16.8725 37.19749 1.50252E-05 0.00090151 0.15 216.3634 78.97266 174.1049 82.58474 Upwelling Bottom TCP4 Up 28.035898Bott -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.01064161 2553.987536 932.2054506 2055.161223 3.10759E-05 0.00186456 0.310759405 447.4935426 163.3351 360.0924 0.000146284 0.00877706 1.463 2106.494 768.8703 1695.069 803.2325 Sett Bott TCP4 Sett28.035898 Bott -80.5809 5/14/2015 19:18 5/15/2015 13:45 0.00359536 862.8856833 314.9532744 694.353113 3.27702E-05 0.00196621 0.327701811 471.8906081 172.2401 379.7244 2.71524E-05 0.00162915 0.272 390.9951 142.7132 314.6288 271.3787 Large Square Large Square28.03748 -80.5795 5/14/15 7:18 PM 5/15/2015 13:45 0.00072333 173.5999972 63.36399896 139.6937054 4.90681E-06 0.00029441 0.049068117 70.65808847 25.7902 56.85766 7.14874E-06 0.00042892 0.071 102.9419 37.5738 82.83604 54.59743 Out Of The Mouth TCB1E 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 7.55887E-05 18.14129526 6.621572771 14.59806911 9.54084E-07 5.7245E-05 0.009540837 13.7388052 5.014664 11.05544 3.05728E-07 1.83437E-05 0.003 4.40249 1.606909 3.542628 1.424403 Into The Mouth TCB1W 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 6.98959E-05 16.77500524 6.122876913 13.49863294 3.16271E-07 1.89763E-05 0.003162708 4.554300066 1.66232 3.664787 8.4866E-07 5.09196E-05 0.008 12.22071 4.460557 9.833846 1.317126 Into The Mouth TCB1W 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 5.88264E-05 14.1183302 5.153190524 11.3608404 2.89915E-07 1.73949E-05 0.002899149 4.17477506 1.523793 3.359388 6.90525E-07 4.14315E-05 0.007 9.943555 3.629398 8.001452 1.108531 Into The Mouth TCB1W 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 7.55887E-05 18.14129526 6.621572771 14.59806911 3.79525E-07 2.27715E-05 0.00379525 5.465160079 1.994783 4.397745 8.80287E-07 5.28172E-05 0.009 12.67614 4.626789 10.20032 1.424403 Settling Bottom TCB1SB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.000426486 102.3565547 37.36014245 82.36501513 1.11789E-06 6.70734E-05 0.011178902 16.09761839 5.875631 12.95355 5.9902E-06 0.000359412 0.06 86.25894 31.48451 69.41147 32.19127 Settling Top TCB1ST 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.000106305 25.5132065 9.312320373 20.53015214 3.37476E-07 2.02486E-05 0.003374763 4.859658381 1.773775 3.910505 1.43427E-06 8.60565E-05 0.014 20.65355 7.538545 16.61965 8.023937 Settling Bottom TCB1SB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 6.58079E-05 15.79388974 5.764769755 12.7091418 3.16384E-07 1.8983E-05 0.00316384 4.555929732 1.662914 3.666099 7.80414E-07 4.68248E-05 0.008 11.23796 4.101855 9.043043 4.967199 Settling Top TCB1ST 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 0.000308791 74.10979031 27.05007346 59.63520383 1.0968E-06 6.58079E-05 0.010967979 15.79388974 5.76477 12.70914 4.04972E-06 0.000242983 0.04 58.3159 21.2853 46.92606 23.30763 Upwelling Bottom TCB1UB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 2.53107E-05 6.074572977 2.217219136 4.888131462 6.32768E-08 3.79661E-06 0.000632768 0.911185946 0.332583 0.73322 3.58569E-07 2.15141E-05 0.004 5.163387 1.884636 4.154912 1.910461 Upwelling Top TCB1UT 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 1.01243E-05 2.429829191 0.886887655 1.955252585 1.26554E-07 7.59322E-06 0.001265536 1.822371893 0.665166 1.466439 4.21845E-08 2.53107E-06 4E-04 0.607457 0.221722 0.488813 0.764185 Upwelling Bottom TCB1UB 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 1.6452E-05 3.948472435 1.441192439 3.17728545 6.32768E-08 3.79661E-06 0.000632768 0.911185946 0.332583 0.73322 2.10923E-07 1.26554E-05 0.002 3.037286 1.10861 2.444066 1.2418 Upwelling Top TCB1UT 28.032073 -80.5825 10/1/2015 16:45 10/3/2015 7:45 2.15141E-05 5.16338703 1.884636266 4.154911742 2.10923E-08 1.26554E-06 0.000210923 0.303728649 0.110861 0.244407 3.37476E-07 2.02486E-05 0.003 4.859658 1.773775 3.910505 1.623892 Out Of The Mouth TCB2E 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 5.41286E-05 12.99085849 4.741663347 10.45357827 6.43634E-07 3.8618E-05 0.006436342 9.268331785 3.382941 7.458108 2.58509E-07 1.55105E-05 0.003 3.722527 1.358722 2.99547 1.020005 Into The Mouth TCB2W 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 2.97549E-05 7.14117367 2.60652839 5.746411447 1.26617E-07 7.59699E-06 0.001266166 1.823278384 0.665497 1.467169 3.69298E-07 2.21579E-05 0.004 5.317895 1.941032 4.279243 0.560705 Into The Mouth TCB2W 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 3.95677E-05 9.496241583 3.466128178 7.641504584 1.47719E-07 8.86316E-06 0.001477193 2.127158115 0.776413 1.711697 5.11742E-07 3.07045E-05 0.005 7.369083 2.689715 5.929808 0.745618 Into The Mouth TCB2W 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 3.7985E-05 9.116391919 3.327483051 7.335844401 1.68822E-07 1.01293E-05 0.001688221 2.431037845 0.887329 1.956225 4.64261E-07 2.78556E-05 0.005 6.685354 2.440154 5.379619 0.715793 Settling Bottom TCB2SB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 5.82645E-05 13.98346953 5.103966378 11.25231973 6.5442E-07 3.92652E-05 0.006544196 9.423642509 3.43963 7.583085 3.16655E-07 1.89993E-05 0.003 4.559827 1.664337 3.669235 4.39782 Settling Top TCB2ST 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 8.23302E-05 19.75925042 7.212126404 15.90001701 1.09774E-06 6.58642E-05 0.010977361 15.80740034 5.769701 12.72001 2.74434E-07 1.6466E-05 0.003 3.95185 1.442425 3.180003 6.214311 Settling Bottom TCB2SB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 5.44646E-05 13.07150413 4.771099006 10.51847279 7.38861E-07 4.43317E-05 0.007388609 10.63959638 3.883453 8.561548 1.68882E-07 1.01329E-05 0.002 2.431908 0.887646 1.956925 4.111005 Settling Top TCB2ST 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 3.41987E-05 8.207688637 2.995806352 6.60462245 4.85537E-07 2.91322E-05 0.004855371 6.991734765 2.551983 5.62616 8.44412E-08 5.06647E-06 8E-04 1.215954 0.443823 0.978463 2.581329 Upwelling Bottom TCB2UB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 2.40658E-05 5.775780893 2.108160026 4.647697279 1.47772E-07 8.86633E-06 0.001477722 2.127919276 0.776691 1.71231 2.53324E-07 1.51994E-05 0.003 3.647862 1.331469 2.935388 1.816491 Upwelling Top TCB2UT 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 4.3065E-05 10.33560791 3.772496888 8.316931974 4.22206E-08 2.53324E-06 0.000422206 0.607976936 0.221912 0.489231 6.7553E-07 4.05318E-05 0.007 9.727631 3.550585 7.827701 3.250562 Upwelling Bottom TCB2UB 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 2.6599E-05 6.383757829 2.330071607 5.136928572 2.11103E-08 1.26662E-06 0.000211103 0.303988468 0.110956 0.244616 4.22206E-07 2.53324E-05 0.004 6.079769 2.219116 4.892313 2.0077 Upwelling Top TCB2UT 28.031683 -80.5823 10/1/2015 17:30 10/3/2015 8:28 8.86633E-05 21.27919276 7.766905358 17.12309524 1.26662E-07 7.59971E-06 0.001266619 1.823930808 0.665735 1.467694 1.35106E-06 8.10636E-05 0.014 19.45526 7.101171 15.6554 6.692334 Out Of The Mouth TCB3E 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 3.58151E-05 8.595631859 3.137405628 6.916795416 4.80705E-07 2.88423E-05 0.004807046 6.92214601 2.526583 5.570163 1.16214E-07 6.97286E-06 0.001 1.673486 0.610822 1.346633 0.674905 Into The Mouth TCB3W 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.000395551 94.93228814 34.65028517 76.39080248 1.4157E-06 8.49421E-05 0.014157014 20.38610034 7.440927 16.40444 5.17682E-06 0.000310609 0.052 74.54619 27.20936 59.98637 7.453813 Into The Mouth TCB3W 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 3.0744E-05 7.378551241 2.693171203 5.937426154 1.84886E-07 1.10932E-05 0.001848864 2.66236385 0.971763 2.14237 3.27513E-07 1.96508E-05 0.003 4.716187 1.721408 3.795056 0.579343 Into The Mouth TCB3W 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.000805999 193.4397506 70.60550896 155.6585022 2.36126E-06 0.000141676 0.023612632 34.00218974 12.4108 27.36113 1.10721E-05 0.000664323 0.111 159.4376 58.19471 128.2974 15.18834 Settling Bottom TCB3SB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.001830079 439.2189423 160.3149139 353.4338856 3.72019E-06 0.000223211 0.037201882 53.57070952 19.55331 43.10767 2.67811E-05 0.001606868 0.268 385.6482 140.7616 310.3262 138.1349 Settling Top TCB3ST 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.000178823 42.91744342 15.66486685 34.5351198 8.87772E-07 5.32663E-05 0.008877722 12.78391932 4.666131 10.28706 2.09261E-06 0.000125556 0.021 30.13352 10.99874 24.24806 13.49759 Settling Bottom TCB3SB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.001681694 403.6065956 147.3164074 324.777084 2.49422E-06 0.000149653 0.024942171 35.9167257 13.1096 28.90173 2.5534E-05 0.001532041 0.255 367.6899 134.2068 295.8754 126.9348 Settling Top TCB3ST 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 5.70711E-05 13.69705641 4.99942559 11.02184674 6.12986E-07 3.67791E-05 0.006129855 8.82699191 3.221852 7.102968 3.38199E-07 2.02919E-05 0.003 4.870065 1.777574 3.918879 4.307743 Upwelling Bottom TCB3UB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 0.000121752 29.22038701 10.66544126 23.51327305 5.91848E-07 3.55109E-05 0.005918481 8.522612878 3.110754 6.858038 1.43735E-06 8.62407E-05 0.014 20.69777 7.554688 16.65524 9.189851 Upwelling Top TCB3UT 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 5.45346E-05 13.08829835 4.777228897 10.53198689 7.18673E-07 4.31204E-05 0.007186727 10.34888707 3.777344 8.327618 1.90237E-07 1.14142E-05 0.002 2.739411 0.999885 2.204369 4.116287 Upwelling Bottom TCB3UB 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 4.18521E-05 10.04450804 3.666245433 8.082687612 4.86161E-07 2.91697E-05 0.00486161 7.000717722 2.555262 5.633388 2.11374E-07 1.26825E-05 0.002 3.04379 1.110983 2.449299 3.159011 Upwelling Top TCB3UT 28.031876 -80.5825 10/1/2015 18:10 10/3/2015 9:05 4.81933E-05 11.56640319 4.221737165 9.30733725 6.34123E-08 3.80474E-06 0.000634123 0.913137094 0.333295 0.73479 7.3981E-07 4.43886E-05 0.007 10.65327 3.888442 8.572547 3.637649

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Appendix II – Background Data

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Chapter 5. Hydrologic and Water Quality Model for Management and Forecasting within Brevard County Waters of the Indian River Lagoon

Gary Zarillo Florida Institute of Technology, Melbourne, Florida 32901

Claudia Listopad Applied Ecology, Inc., Indian Harbour Beach, Florida 32937

5.1. Summary

A coupled hydrodynamic-water quality model of the Indian River Lagoon is designed as a tool for understanding the ecology, maintaining water quality goals, and forecasting the potential benefits of management strategies, including muck dredging. The overall goal is to integrate water quality and physical process data into the coupled model of the IRL for long-term calibrated and validated predictions of water quality. Questions to be answered include: 1) whether muck dredging will improve local water quality in the vicinity of Turkey Creek and other localities that are to be dredged over the next several years, 2) whether improved model guidance by measured in situ data and modeled watershed data will allow the relative effects of watershed inputs and nutrient flux from muck sediments to be resolved, 3) if muck dredging, either locally or regionally, can result in a lasting improvement of IRL water quality. Project tasks are aimed at evaluating the benefits of muck dredging in the north and central Indian River Lagoon, among other issues.

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of Technology Final Report, July 2016 the first half of a 2-year model run. Other water quality variables are also calculated including forms of phosphorus, dissolved oxygen, and several others. These model data along with values for nitrogen components are stored in model data archives for further analysis.

5.2 Introduction and Goals The goal of this project is to deploy a full three-dimensional combined hydrodynamic and water quality model in the Indian River Lagoon to answer the following questions: 1) whether muck dredging will improve local water quality in the vicinity of Turkey Creek and other localities that are to be dredged over the next several years, 2) whether improved model guidance by measured in situ data and modeled watershed data will allow the relative effects of watershed inputs and nutrient flux from muck sediments to be resolved, 3) if muck dredging either locally or regionally can result in a lasting improvement of IRL water quality. The modeling effort consists of three major software platforms including a three dimensional hydrodynamic model, a water quality or eutrophication model, and a watershed model to provide inputs to the combined hydrodynamic and water quality models.

5.3 Methods 5.3.1. Hydrodynamic Model Overview The model applied to meet the project objectives is the EPA supported Environmental Fluid Dynamics Code/Hydrodynamic and Eutrophication Three-Dimensional Model (EFDC/HEM3D). EFDC/HEM3D includes features and capabilities that make it superior and more applicable to shallow estuarine environments than other models. The project area extends from the Mosquito Lagoon into the main body of the IRL extending to Ft Pierce Inlet. EFDC/HEM3D was developed and refined at the Virginia Institute of Marine Science over the time period of 1988- 1995 (Hamrick, 1992). This multi-parameter finite difference model represents estuarine flow and material transport in three dimensions and has been extensively applied to shallow estuarine environments in Florida and other coastal states. A few examples include the central Indian River Lagoon (Zarillo and Surak, 1994, Zarillo and Yuk, 1996); Long Slip Canal, Hudson River (Zarillo, 1999); Lake Jesup, FL ( Zarillo, 2001); the Loxahatchee River Estuary in South Florida (Zarillo, 2004); Lake Worth, FL (Zarillo, 2003); the lower Savannah River, GA (Tetra Tech, 2005); the Peconic Estuary, Long Island New York (Tetra Tech, 2000); the York River, VA (Sisson et al., 1997), the German Wadden Sea (Zarillo, 1997).

The details of the EFDC’s hydrodynamic scheme can be found in technical manuals and users guides published with support of the U.S. EPA (Tetra Tetra, 2000) and within publications by Hamrick (1992, 1994). Figure 5.1 shows a flow diagram of the various model components of the EFDC model. The EFDC model can be used to drive a number of external water quality models using internal linkage processing procedures described in Hamrick (1992).

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Figure 1. Flow diagram for the EFDC hydrodynamic and transport model. Drifter, dye, and near field plume calculations are driven by subroutines within the main body of the EFDC model.

5.3.2. Model Overview - Water Quality Calculations The EFDC model can be directly coupled with the water quality model. The kinetic processes included in the HEM3D water quality model have been derived and updated from the Chesapeake Bay three-dimensional water quality model, CE-QUAL-ICM (Cerco and Cole, 1994). A detailed description of the water quality model is provided by Park et al. (1995) and Tetra Tech (2007). Table 5.1 lists the model's complete set of state variables. Figure 5.2 presents a schematic flow chart of interactions among water quality variables in EFDC/HEM3D. Earlier water quality models, such as WASP (Ambrose et al., 1993) used biochemical oxygen demand (BOD) to represent oxygen demanding organic material, whereas the HEM3D water quality model is carbon based. The algae species are represented in carbon units. The three organic carbon state variables play an equivalent role to BOD, including dissolved, labile particulate, and refractory particulate. Organic carbon, nitrogen and phosphorous can be represented by up to three reactive sub-classes, refractory particulate, labile particulate and labile dissolved. The use of the sub-classes allows a more realistic distribution of organic material by reactive classes when data are used to estimate distribution factors. The following brief sections discuss the role of each variable and summarize the kinetic interaction processes. The kinetic sources and sinks, as well as the external loads for each state variable, are fully described in Park et al. (1995). Kinetic processes include the exchange of fluxes at the sediment-water interface, including sediment oxygen demand. Formulations of these processes in the EFDC water quality model are also discussed in Park et al. (1995).

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Table 5.1. List of water quality variables that can be calculated by the EFDC/HEM3D model.

(1) cyanobacteria Bc (12) labile particulate organic nitrogen LPON

(2) diatom algae Bd (13) dissolved organic nitrogen DON

(3) green algae Bg (14) ammonia nitrogen NH4

(4) refractory particulate organic carbon RPOC (15) nitrate nitrogen NO3

(5) labile particulate organic carbon LPOC (16) particulate biogenic silica SAP

(6) dissolved organic carbon DOC (17) dissolved available silica SAD (7) refractory particulate org. phosphorus RPOP (18) chemical oxygen demand COD

(8) labile particulate organic phosphorus (19) dissolved oxygen DO

(9) dissolved organic phosphorus DOP (20) total active metal TAM

(10) total phosphate TP (21) fecal coliform bacteria FCB (11) refractory particulate organic nitrogen RPON

Figure 5 2. Flowchart for the water quality module of HEM3D.

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Algae

Algae are grouped into four model classes: cyanobacteria, diatoms, greens, and stationary that can be differentiated in the model calculations. The grouping is based upon the distinctive characteristics of each class and upon the significant role the characteristics play in the ecosystem. Cyanobacteria, commonly called blue-green algae, are characterized by their abundance (as picoplankton) in saline water and by their bloom-forming characteristics in fresh water. Cyanobacteria are unique in that some species fix atmospheric nitrogen, although nitrogen fixers are not believed to be predominant in many river systems. Diatoms are distinguished by their requirement of silica as a nutrient to form cell walls. Diatoms are large algae characterized by high settling velocities. Settling of spring diatom blooms to the sediments may be a significant source of carbon for sediment oxygen demand. Algae that do not fall into the preceding two groups are lumped into the heading of green algae. Green algae settle at a rate intermediate between cyanobacteria and diatoms and are subject to greater grazing pressure than cyanobacteria. A stationary or non-transported algae variable is included in the model and has been used to simulate macroalgae. The stationary algae variable has the same kinetic formulation as the original algae groups, with the exception that it is not transported. The stationary algae group can also be used for various types of bottom substrate attached or floating periphyton.

Organic Carbon Three organic carbon state variables are considered: dissolved, labile particulate, and refractory particulate. Labile and refractory distinctions are based upon the time scale of decomposition. Labile organic carbon decomposes on a time scale of days to weeks whereas refractory organic carbon requires more time, on the order of months to years. Labile organic carbon decomposes rapidly in the water column or the sediments. Refractory organic carbon decomposes slowly, primarily in the sediments, and may contribute to sediment oxygen demand years after deposition.

Nitrogen Nitrogen is first divided into organic and mineral fractions. Organic nitrogen state variables are dissolved organic nitrogen, labile particulate organic nitrogen, and refractory particulate organic nitrogen. Two mineral nitrogen forms are considered: ammonium and nitrate. Both are utilized to satisfy algal nutrient requirements. The primary reason for distinguishing the two is that ammonium is oxidized by nitrifying bacteria into nitrate. This oxidation can be a significant sink of oxygen in the water column and sediments. An intermediate in the complete oxidation of ammonium, nitrite, also exists. Nitrite concentrations are usually much less than nitrate. Thus for modeling purposes, nitrite is combined with nitrate. Hence, the nitrate state variable actually represents the sum of nitrate plus nitrite.

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Phosphorus As with carbon and nitrogen, organic phosphorus is considered in three states: dissolved, labile particulate, and refractory particulate. Only a single mineral form, total phosphate, is considered. Total phosphate exists as several states within the model ecosystem: dissolved phosphate, phosphate sorbed and absorbed to inorganic solids, and phosphate incorporated in algal cells. Adjustable equilibrium partition coefficients are used to distribute the total among the three states.

Silica Silica is divided into two state variables: available silica and particulate biogenic silica. Available silica is primarily dissolved and can be utilized by diatoms. Particulate biogenic silica cannot be utilized. In the model, particulate biogenic silica is produced through diatom mortality. Particulate biogenic silica undergoes dissolution to available silica or else settles to the bottom sediments.

Chemical Oxygen Demand In the context of this study, chemical oxygen demand is the concentration of reduced substances that are oxidizable by inorganic means. The primary component of chemical oxygen demand is sulfide released from sediments. Oxidation of sulfide to sulfate may remove substantial quantities of dissolved oxygen from the water column.

Dissolved Oxygen Dissolved oxygen is required for the existence of higher life forms. Oxygen availability determines the distribution of organisms and the flow of energy and nutrients in an ecosystem. Dissolved oxygen is a central component of the water quality model and is closely linked to the activity of other water quality constituents, low oxygen and anoxic conditions can result from excessive nutrient loading and eutrophication

Total Active Metals Both phosphate and dissolved silica adsorb onto inorganic solids, primarily iron and manganese. Sorption and subsequent settling is one pathway for removal of phosphate and silica from the water column. Consequently, the concentration and transport of iron and manganese are represented in the model. However, limited data do not allow a complete treatment of iron and manganese chemistry. Rather, a single-state variable, total active metal is defined as the total concentration of metals that are active in phosphate and silica transport. Total active metal is partitioned between particulate and dissolved phases by an oxygen-dependent partition coefficient. Inorganic suspended solids can be used, in lieu of total active metal, as a sorption site for phosphate and silica. Inorganic suspended solids concentration can be provided by the sediment transport component of the EFDC modeling system.

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5.3.3. Spatial Watershed Iterative Loading (SWIL) model The Spatial Watershed Iterative Loading (SWIL) model is a custom ESRI ArcGIS toolset, providing a continuous monthly simulation of runoff (surface and baseflows) yielding robust representation of pollutant loadings and freshwater volumes to the IRL. SWIL was developed by Dr. Claudia Listopad of Applied Ecology, Inc. Details of model operation can be found in the SWIL Model Methodology Manual (Applied Ecology, Inc., 2015). The SWIL model was developed as part of this study to incorporate available watershed data into the TMDL process.

The SWIL model has been updated since the initial version was developed in 2012 (SWIL 1.0). By July 2014, SWIL 2.0 was released focusing on addressing initial FDEP comments, improving the ease of execution and reducing the overall processing time. SWIL 3.0, released in April 2015, focused on improving model calibration to the measured available gage data, which included a change in the methodology to derive baseflow volumes and loads. SWIL 3.0 also incorporated the newly released evapotranspiration (ET) raster datasets. For additional details on the changes included in the latter changes of SWIL, please review the Model Methodology Manual (Applied Ecology, Inc. 2015). SWIL 3.0 is applied in this study, but includes some spatial refinements to better fit the spatial coverage of the EFDC.HEM3D model grid. The SWILL model does not account for atmospheric inputs or point source loadings, which are handled by other components of the model.

5.3.4. Hydrodynamic and Water Quality Model Grid Generation The model grid was designed as a theme in the ArcGIS software platform. A recent set of aerial images was used as a background over which a data layer was hand drawn to fit the model grid to shoreline boundaries and other morphologic features of the IRL system. Care was taken to include extensive marsh and mangrove areas as well as include the details of the numerous causeway-bridge combinations of the system. The EFDC/HEM3D model includes a separate grid generator computer code. Once a grid is visualized as a GIS layer, the grid generator uses an array of cell types and the x,y coordinates of the corner points of all water cells to produce model input files that numerically represent the model grid. A time consuming step in the grid generation process can be to digitize the water cell corner points. To speed this process, Applied Ecology, Inc. developed a digitizing tool that operates under ESRI ArcGIS 10.3. The hand drawn grid layer is opened by the tool and the coordinates of the cell corner points are digitized in order, row by row from the southwest corner of the grid to the northeast corner of the grid. The grid tool assigns I (row) and J (column) indices to each set of cell coordinates. The subscripted list of cell coordinates along with an ordered 2-dimensional array of cell types, and depth value inputs are then used by the grid generator to calculate an ordered list of cell dimensions (file dxdy.out) and a file specifying horizontal cell center coordinates and cell orientations (file lxly.out). These files are restated as input files, and along with control and boundary forcing information, are used to run both the hydrodynamic and water quality calculations.

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The extent of the model domain allows an integrated evaluation of water quality interactions among the major basins of the IRL and incorporates all major areas of muck deposits. Figure 5.3 shows the geographic extent of the EFDC model grid from near Ponce de Leon Inlet on the north and Ft. Pierce Inlet on the south. The grid dimensions are stated in UTM metric coordinates and depth values are in the NAVD88 vertical datum. The details of the model grid in the Turkey Creek area of Brevard County are shown in Figure 5.4 At the time of this report the combined hydrodynamic and water quality model includes about 9,400 computational cells in the horizontal along with 5 vertical layers, each representing 20% of the water column.

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Figure 5.4. Model grid in the Turkey Creek area. 5.3.5. Hydrodynamic Model Inputs Data sets have been assembled from a wide range of sources and evaluated for use in the model. Figure 5.5 shows the distribution of monitoring stations managed by the SJRWMD. These data from stations include time series of water level, salinity, temperature, discharge and meteorological parameters. Water quality data at approximate monthly intervals are also available from the SJRWMD. These data have been assembled into a large ongoing database that can be used to extract data for model boundary conditions as well as for calibration.

Data in time series format are required to force the model at open boundaries. Other forcing includes surface water inflows and base flows from the watershed model that approximate groundwater influx. Data from meteorological stations maintained by the SJRWMD are used to setup air-sea interaction boundary conditions input to the hydrodynamic model. Table 5.2 lists the major input files used to run the hydrodynamics of EFDC and their function.

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Figure 5.5. Long term IRL monitoring stations for freshwater, water level, salinity and water temperature.

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Table 5.2. Hydrodynamic and transport input files

Input Description Status File aser.inp Atmospheric forcing time-series Complete file. cell.inp Horizontal cell type identifier file. Complete dxdy.inp File specifying horizontal grid Complete spacing or metrics, depth, bottom elevation, bottom roughness and vegetation classes for either Cartesian or curvilinear orthogonal horizontal grids. lxly.inp File specifying horizontal cell Complete center coordinates and cell orientations. pser.inp Water level time series Complete qser.inp Volumetric source-sink time-series Complete file. (inflow-outflow) salt.inp File with initial salinity distribution Complete for cold start, salinity stratified flow simulations. sser.inp Salinity time-series file. Complete tser.inp Temperature time-series file Complete

For each of the time series files listed in Table 5.2, the complete available data record is loaded in the model boundary input file. For instance, Figure 5.6 shows the water level time series loaded into file pser.inp at the north open boundary of the model at north end of Mosquito Lagoon and the south boundary near Ft. Pierce Inlet (See Figure 5.5). Likewise Figure 5.7 shows salinity time series from these monitoring stations loaded into file sser.inp (Table 5.2). Although the data sets are of high quality, having been quality controlled levelled to NAVD88 with respect to water level, they are limited in time span. Thus to force the model outside of the 3-year periods from August 1997 through August 2000, other data sources or methods must be developed. As of February 2014 the water level time series open boundaries have been extended by about 6 months using tidal water level oscillation predicted using known tidal constituents established near the model boundaries from NOAA water level data. Predicted tide elevation time series are centered about a mean elevation of 0. To add a vertical datum and account for the low frequency, non-tidal sea level oscillations that propagate though the coastal ocean and into estuaries, low pass filtered water level data from the long term station at Trident Pier, Cape Canaveral and the Florida Tech Water level gauge at Sebastian Inlet are added to the constituent based water level record. Previous experience has shown that water level data by this method can result in good model calibration results (Zarillo et al., 2010).

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However, to bring the model performance up to the present day and beyond, the model grid in year 2 of the project will be extended into the nearshore coastal ocean using combined tidal and low frequency water level data, and assuming full or near ocean salinity of about 33 to 35 psu.

Figure 5.6. Water level time series applied in file to force north and south model boundaries. Annual highstand of sea level seen in October 1999 is included in model calibration (see Figure 5.12).

Figure 5.7. Surface salinity time series applied in model, along with near- bottom salinity data to force north and south model boundaries

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5.3.6. Water Quality Model Setup To activate the water quality calculations within EFDC/HEM3D, various input files are applied and controls set in the main input file (EFDC.INP). Table 5.4 lists the required files and their function within the model. Similar to the hydrodynamic portion of the model, water quality data to drive and calibrate the model are derived from existing historical sources, on-going data collection effort sponsored by the SJRWMD and the SWIL watershed model (Applied Ecology, 2015). Figure 5.5 shows the distribution of water quality monitoring stations maintained throughout the IRL system.

The water quality parameter concentrations and coefficients controlling the kinetics of the nutrient and sediment cycles initially have been set from a review of all available water quality data from the IRL. During the calibration process, kinetics and coefficients for each variable are adjusted where necessary. For example, kinetics constants and coefficients for the water column and sediment model input files are adjusted for model calibration and operation using information collected during year 1 of the project to determine the environmental impacts of muck dredging

Table 5.3. Summary of Major EFDC/HEM3D Water Quality Input Files

Model Input Description Status File efdc.inp Primary controlling input file Complete for EFDC hydrodynamics and water quality transport options wq3dwc.inp Kinetics constants and Operational pending input coefficients for the water from IRLRI Team column wq3dsd.inp Kinetics constants and Operational pending input coefficients for the sediment from IRLRI Team model cwqsr01- Time-series tidal boundary Complete 21.inp conditions for water quality state variables 1-21 wqpsl.inp Time -series river and point Operational source loads for variables 1-21

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Figure 5.8. Location of water quality monitoring station maintained by the SJRWMD. 5.3.7. Watershed Inputs

Watershed inputs are assembled from the Spatial Watershed Iterative Loading (SWIL) Model developed by Applied Ecology, Inc. Figure 5.9 shows the watershed sub-basins linked to the IRL model. Time series of surface water flows, base flows, and major nutrient classes produced by the SWIL model are applied as inputs to model runs, along with freshwater inflows from major USGS gauging stations associated with water control structures connected to Turkey Creek and the Sebastian River. Surface water, baseflow, and USGS gauged flow data are placed in model input file qser.inp (see Table 5.2). At present there are no estimates of nutrient or sediment concentrations associated with the USGS gauged flows.

SWIL watershed model output is available as monthly loads of total phosphorus and total nitrogen from 1995 through 2011. Likewise, storm water runoff and baseflow volumes are provided as monthly volumes. Figure 5.10 shows an example of output from the SWIL water shed model from the Turkey Creek sub-basin.

Time series of water quality data from SWIL and from selected SJRWMD monitoring stations are specified as input to the EFDC/HEM3D model in file wqpsl.inp (see Table 5.3). In this file,

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Figure 5.9. Boundaries of the watershed model sub-basin links to the IRL model. Barrier Island watersheds are not included.

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Figure 5.10. Example of total nitrogen and total phosphorus inputs to the EFDC/HEM3D model from the SWIL watershed model from 1994 to 2010. Inputs are received from the Turkey Creek sub-basin

5.3.8. Sediment Diagenesis Model Setup for Muck Assessment The EFDC sediment diagenesis model is based on formulations modified from the Chesapeake Bay model and includes 27 state variables and fluxes (Table 5.4). This sub model is a key element in assessing the benefit of muck dredging. Three basic processes are included in the sediment sub model: depositional flux of particulate organic matter (POM) from water column, diagenesis (decay) of POM in sediments, and flux of substances produced by diagenesis. Benthic sediments are represented by two layers. The upper layer can be oxic or anoxic, whereas the lower layer is always anoxic. The diagenesis model is schematically represented in Figure 5.11.

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Table 5.4. Sediment model state variables

(1) particulate organic carbon G1 class in layer 2 (15) nitrate nitrogen in layer 1 (2) particulate organic carbon G2 class in layer 2 (16) nitrate nitrogen in layer 2 (3) particulate organic carbonG3 class in layer 2 (17) phosphate phosphorus in layer 1 (4) particulate organic nitrogen G1 in layer 2 (18) phosphate phosphorus in layer 2 (5) particulate organic nitrogen G2 in G2layer 2 (19) available silica in layer 1 (6) particulate organic nitrogen G3 in layer 2 (20) available silica in layer 2 (7) particulate organic phosphorus G1 in layer 2 (21) ammonia nitrogen flux (8) particulate organic phosphorus G2in layer 2 (22) nitrate nitrogen flux (9) particulate organic phosphorus G3 in layer 2 (23) phosphate phosphorus flux (10) particulate biogenic silica in layer 2 (24) silica flux (11) sulfide/methane in layer 1 (25) sediment oxygen demand (12) sulfide/methane in layer 2 (26) release of chemical oxygen demand (13) ammonia nitrogen in layer 1 (27) sediment temperature (14) ammonia nitrogen in layer 2

Figure 5.11. Sediment diagenesis schematic. Sub-bottom processs include two layers.

The kinetics of the sediment model are controlled within file wq3dsd.inp listed in Table 5.3. The recent data collected by Dr. Trefry’s team and described in Chapter 2 of this report indicate high rates of loading of ammonium and phosphate to the water column by muck sediments (Trefry et al., 2015). The Trefry team is also performing laboratory experiments of nutrient flux from muck sediments sampled from the area of Turkey Creek to be dredged. Within the sediment diagenesis model, fluxes of these and other nutrients are accordingly specified for model runs to assess present conditions. In ongoing model experiments described in a later section, nutrient fluxes from the bottom

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sediments are hypothetically adjusted to represent nutrient release after dredging of muck from Turkey Creek.

5.4 Results 5.4.1. Hydrodynamic Model Validation To assure the accuracy of the model within the limitations of the observational data, model predicted data were compared with measured data over selected historical time periods. Below are example comparisons between predicted and model data

5.4.2. Calibration of Physical Processes Figure 5.12 shows the comparison between predicted and measured water level data near the mouth of the Sebastian River for the historical 1999 calibration period. In this area, the tidal signal is damped due to the morphologic restrictions of Sebastian Inlet. However, the water level curve in Figure 5.12 shows a large low frequency oscillation over a range of about 40 cm along with shorter term spikes in water level due to local wind effects. Such lower frequency shifts in sea level are related to passing of weather systems and changes in Gulf Steam flux that have been correlated with variations in non-tidal sea level of up to 1 m on a seasonal time frame.

The water level record Figure 5.12 shows the typical seasonal shift in sea level that occurs between mid-July and mid-October each year. In 1999 sea level increased from a low of about -0.4m relative to NAVD88 to a persistent high stand at about +0.2m NAVD88. Shorter term events pushed sea level to above 0.5m for a day or two. At the end of October sea level usually undergoes a drop of about 0. 4m over a 2-week period, as demonstrated by the record in Figure 5.12. Although narrow and shallow inlets such as Ponce Inlet and Sebastian Inlet can damp the astronomical tides and severely reduce the tidal range of an interior location like the lower Sebastian River, low frequency sea shifts are readily transmitted through to the back barrier. By comparison, water level changes due to rainfall, freshwater inflows from water control structures and manipulation of mangrove impoundments are of secondary importance and local in extent.

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Figure 5.12. Model and measured water level comparison in the Sebastian River.

5.4.3. Calibration of Transport Processes A number of transport processes are included in EFDC model code including salt and heat, sediment, and Lagrangian calculations for generic tracers that can be used for numerical flushing experiments. In this project, the IRL model is calibrated for salinity and water temperature with assumption that other transport processes that may be calculated will also have a similar verification level. Figure 5.13 is an example of a calibration model run for salinity calculations in the lower Sebastian River.

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Figure 5.13. Comparison of measured and model salinity at the mouth of Sebastian River. 5.4.4. Calibration Statistics The statistics applied to check the match between predicted water level, salinity and temperature at the lower Sebastian River calibration station included the root mean square error (RMSE) and the ratio between RMSE and the range (RANGE) of observed values of each variable during the calibration and validation periods. The RMSE/Range provides a comparison in a percentage format. The formulation of RMSE as shown below is the square root of the average squared differences between observed and predicted parameter values. In the formula

2 RMSE: (O  P) / N ,

Where O is the observed value, P is the predicted value and N is the number of observations.

The validation period is May to early December 1999, whereas the verification period is from January to early June 2000. Calibration adjustments to the model included incrementally adjusting the mean water elevation at the open boundaries of the model and local adjustments of a boundary roughness height to influence exchanges through the model open boundaries. Once adjustments are made for the calibration period model runs, no further changes are made in model parameter before performing data-model comparisons for the verification periods.

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Table 5.5 lists data-model comparison for an initial calibration and subsequent verification period for water level, salinity and temperature in the lower Sebastian River. Based on the model validation results, the EFDC hydrodynamic predictions have good match with measured data. Further adjustments to model boundary conditions and controls will be made throughout the project to improve calibration. It is likely that some refinements and adjustments to the existing model grid will be made to better accommodate the footprint and magnitude of muck dredging project.

Table 5.5. Statistics of model-data comparisons in the lower Sebastian River for calibration and verification

Calibration Period Verification Period

Parameter RMSE RMSE/Range RMSE RMSE/Range

Water level 0.08 m 7.7% 0.09 m 9.4%

Salinity 4.7 psu 16.6% 5.6 psu 17.3% surface

Salinity 0.8 psu 4.8% 1.5 psu 4.1% bottom Temperature o 8.2% o 4.2%% bottom 1.8 C 0.76 C

Temperature o 10.9% o 15.7% surface 2.09 C 2.8 C

5.4.5. Water Quality Model Validation Calibration and verification the EFDC/HEM3D water quality and eutrophication calculations are ongoing at the time of this writing. The Sediment Diagenesis Model is being adjusted and recalibrated for the flux of nutrients from muck sediments based on the work of John Trefry described in Chapter 3 of this report. New model runs are initiated and once complete, comparisons will be made between a suite of predicted and measured nutrient constituents, including forms of nitrogen, phosphorus, ammonia nitrogen and dissolved oxygen. However, even without detailed adjustment and calibration of the water quality and sediment sub-models, results have been encouraging. Dissolved oxygen (DO) levels are linked to the concentration and activity of other water quality components. Low oxygen and anoxic conditions are linked to excessive nutrient loading and eutrophication. Thus, a comparison of measured and predicted DO provides a guide to water quality model performance.

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Figure 5.14 is an example of water quality model output for dissolved oxygen in the central IRL between Melbourne and Turkey Creek. Model output for a 1999 calibration period is compared to measured dissolved oxygen values. Predicted model values are shown for model layers 1 (lower) to layer 5 (upper). Superimposed on the longer term trend are daily oscillations that are characteristic of DO values. Similar to other water quality data DO values are collected at low spatial and temporal resolution. There are too few measured data to validate the model trends and variability.

When available, the measured data correspond well to the predicted data. Measured data are contained within the predicted data that are plotted in Figure 5.14 from model layer 1 (bottom) to model layer 5 (surface). Measured data that plot on the same date are likely to have been collected at more than one depth, one near-surface and one near-bottom. These multiple data points are captured by one of the model layers. Overall, the model results indicate that D.O. predictions are likely to be accurate and can be used to evaluate that aspect of water quality to help assess the efficacy of muck dredging in Turkey Creek and other areas.

Figure 5.14. Comparison of measured and predicted dissolved oxygen values for a 1999 calibration period.

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5.4.6. Model Simulations in the Central IRL Calibration of the water quality model is ongoing. Further adjustments will be made based on analysis of muck nutrient dynamics discussed in Chapter 3. The coupled hydrodynamic and water quality model (HEFDC/HEM3D) driven by boundary conditions and watershed inputs is being tested for sensitivity to nutrient flux from muck sediments into the water column above. Model runs were setup to represent up to 3 years of real time in order to examine water quality conditions specific to the Turkey Creek and nearby area of the Indian River Lagoon. To accomplish this, sediment digenesis sub-domains were setup in the model to include the lower portion of Turkey Creek and about 10 square km of the central IRL, beyond the entrance of Turkey Creek. Two separate runs were launched. Model Case 1 includes existing conditions with respect to watershed inputs, baseflows, and gauged freshwater flow into Turkey Creek from the C-1 control structure. Nutrient flux from the benthic boundary of Turkey Creek was approximately set according to fluxes and reported by Dr. John Trefry and his research group in Chapter 3. The constituent being adjusted within the sediment diagenesis model is the flux of ammonium to the water column. It is reported that the equivalent of 15 metric tons annually per km2 is being contributed to the water column from the interior of Turkey Creek (Chapter 3 of this report). This result compares to the IRL average of 8 metric tons annually per km2, and a rate of 12 metric tons annually per km2 for Eau Gallie Harbor to the north (Trefry, personal communication). Thus, for the existing model case, the sediment diagenesis subdomain that includes Turkey Creek was set to have a vertical ammonium flux equivalent to the nitrogen loading, but stated in g per m2 per day. In the regional sediment diagenesis domain surrounding Turkey Creek the flux was set to be equivalent to the IRL average.

Model Case 2 assumes a 50% reduction in the ammonium-based nitrogen flux from muck sediment to the water column. This scenario was designed to test the sensitivity of the model to potentially large changes in nutrient contributions that may be associated with muck dredging within Turkey Creek, An additional model case involving a 90% reduction of ammonium based nitrogen flux from Turkey Creek (Case 3) has also been launched.

As of this report the model runs are still underway. Numerical model time step adjustments have been required to keep the model stable. Decreases in numerical time step have slowed the progress of model runs. However, as of this writing model runs are being converted to parallel processing to increase the speed of computations. It is expected that use of the Florida Tech Blue Marlin Beowulf cluster will substantially decrease computational time required for each run.

Figure 5.15 shows an example of a prediction from the initial run of Model Case 1, which approximates present pre-dredge nutrient loading conditions. The total P and N values were extracted from a numerical station approximately 5 km south of Turkey Creek entrance.

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Figure 5.15. Five month time series of predicted total N and total P concentrations under pre-dredge conditions from a numerical observation station about 5 km south of Turkey Creek entrance

Figure 5.16 shows predicted total nitrogen values over a 20 month period at the entrance of Turkey Creek. Model results are shown for the case of existing nitrogen loading from ammonium flux and model Case 2 in which nitrogen loading from ammonium as specified in the controls of the EFDC sediment diagenesis model has been hypothetically reduced by 50%. Over the course of the 20-month simulation, predicted nitrogen concentrations in the water column, existing condition and hypothetical, are expected to track in parallel to each other; the existing condition showing the higher concentration during the simulation.

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Figure 5.16. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located in the entrance of Turkey Creek

Predicted total nitrogen values from a central lagoon location about 4 km north of Turkey Creek entrance are shown in Figure 5.17. The alternative is the same as represented in Figure 5.16. Nitrogen loading from ammonium flux to the water column is specified to be reduced by 50% in the sediment digenesis model. At this station about 4 km from Turkey entrance where ammonium flux is reduced to approximate results of dredging, the difference between the existing and reduced load case is not as marked. The predicted total nitrogen concentration for reduced ammonium flux remains slightly below concentration for the existing condition for the first half of the simulation. However, for the second half of the model run, predicted concentrations are on the average similar outside of some temporal variability. For the final few weeks of simulation, nitrogen concentrations for the existing case dropped slightly over 0.1 mg/L below those for the alternative case, before beginning to recover. There is a trend of a slight decrease in nitrogen concentration over about the first six months of the model run period.

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Figure 5.17. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located about 4 km north of Turkey Creek entrance.

Figures 5.18 and 5.19 show predicted nitrogen values at numerical model stations located about 4 km and 10 km south of Turkey Creek entrance. The time series pattern predicted at the station 4 km south of Turkey Creek is similar to that shown in Figure 5.16 for the Creek entrance. Short time scale variations on the order of a few days are superimposed on longer-term trends. Variability is likely due to diurnal variations in wind, water temperature, along with slightly longer term synoptic variations in water level. There is a trend of slightly increasing concentration and an overall net increase of about 0.1 to 0.2 mg/L in total nitrogen concentration. Overall, the signature of the hypothetical reduction in ammonium based nitrogen flux within Turkey Creek entrance is modulated at the station 4 km south shown in Figure 5.18.

At the station 10 km south the pattern is different than those of stations closer to Turkey Creek entrance. Here, there is a net decrease in predicted nitrogen concentration of about 0.35 mg/L over the course of the model run, but included a period of stability in the middle of the simulation. A decrease in N concentration occurred at the beginning and end of the predicted time series. Predicted N concentration for the reduced ammonium case within Turkey Creek are below the existing case for the first 5 months of the simulation and then track closely with the existing case for the remainder of the simulation.

As model predictions continue and as more pre- and post-dredging nutrient data from Turkey Creek become available, model results will be examined within the larger context of other factors that influence nitrogen concentration in the central IRL.

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Figure 5.18. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located about 4 km south of Turkey Creek entrance.

Figure 5.19. Prediction of total nitrogen concentrations over an approximate 20-month period at numerical observation station located about 10 km south of Turkey Creek entrance.

The ongoing prognostic model runs will examine longer term variability and trends of IRL water quality for existing conditions and hypothetical conditions in which the interaction of muck sediments with the water volume is adjusted for muck removal. The ongoing work by the IRLRI along with the body of historical data are critical to the operation of the EFDC/HEM3D model. With improved watershed and implementation of sediment transport calculations in year 2 of this

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of Technology Final Report, July 2016 project, the EFDC-HEM3D model could be driven into the future by using climatologic (characteristic) data developed from historical data and watershed modeling.

5.5 Project Quality Control The quality of model predictions is ultimately demonstrated by the statistics provided from comparisons between measured and model data described under Section 5.4 of this report. The first year of this project was largely one of model setup and model validation, followed by initial model results. The model validation process will continue throughout the project as new data sets are added to the model boundaries and new water quality data are collected by the ongoing Florida Tech Environmental Muck Dredging Research Project that can be used for both calibration and boundary conditions.

Beyond the model validation process it is important to consider the measured data that support the model boundaries and calibration. There are two categories of measured data that need to be considered. For the model setup to date, much of the data are provided by the monitoring programs in the Indian River Lagoon Basin either sponsored by, or directly conducted by the SJRWMD. One data type is hydrologic data including water level and water discharge from tributaries and water control structures that connect with the IRL. These data are collected by the U.S. Geological Survey (USGS). The second, and equally important category is water quality data that can range from salinity and temperature measurements to a full pallet of nutrient constituents. Watershed inputs from the SWIL model should also be under quality control. The following sections address the quality control plans for the various model input data types

5.5.1. U.S. Geological Survey Hydrologic Data The SJRWMD maintains a cooperative agreement with the USGS to maintain near real time observations of water level and surface water discharge within the IRL Basin. Historical and current stations maintained by the USGS are shown in Figure 5.5. The USGS has published a series of manuals on Techniques and Methods (TM) describing approved scientific and data- collection procedures and standard methods for planning and deploying monitoring stations (Sauer and Turnipseed, 2010; Turnipseed and Sauer, 2010). The material in the manuals is grouped under major subject headings called “books” and further subdivided into sections and chapters. For instance Chapter 7 of book 3, Section A (TM3-A7) covers all aspect of stage measurements at USGS gaging stations. Likewise Chapter 8 of book 3, Section 8 (TM3-A8) describes methodology for discharge measurements at USGS gaging stations. These and other USGS publications on hydrologic data collection can be found at http://water.usgs.gov/admin/memo/SW/. In addition to describing the methods of hydrologic data collection, the manuals include quality assurance and quality control sections that present

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of Technology Final Report, July 2016 discussion of accuracy requirements, sources of error, and error mitigation procedures, and equipment maintenance.

5.5.2. Quality Assurance for the SWIL Watershed model Quality procedures for the SWIL watershed model are presented in an extensive technical document by Engineering Research & Design, Inc. (ERD, 2012). The EDR report deals with refinement of the SWIL model for application to TMDL calculations. SWIL model outputs are evaluated for accuracy by a comparison of measured versus model parameters. Calibration procedures are described in Section 4 of the ERD report.

5.5.3. Quality Assurance for SJRWMD water quality data Quality assurance for water quality parameters is covered by the SJRWMD Field Standard Operating Procedures for Surface Water Sampling (FSOP). There is one standard document containing procedures for environmental sampling that is reviewed annually and revised as necessary (SJRWMD, 2015). The SJRWMD FSOP generally follows the Florida Department of Environmental Protection (FDEP) SOPs for field data activities.

Issues relating to quality assurance are distributed throughout the SJRWMD FSOP document. Among the many topics covered in the SJRWM FSOP are instrument maintenance, instrument calibration, field methods, and sample chain of command. A section is also provided on data review and assessment including procedures for internal and external audits of data sets. Within data review sections of the FSOP are descriptions of actions for data quality issues that may arise.

5.6 Conclusions Modelling tasks completed include assembly of relevant hydrologic and water quality data, development of the model grid, coupling of the SWIL watershed model, model calibration, and several model production runs. Care was taken to add important details in the model grid including bridge-causeway structures, mangroves flats and wetlands, and narrow canals such as Haulover Canal. Freshwater inflows are also carefully added from stream flow data gages by the USGS and watershed runoff from the SWIL model that have been calibrated. These details insure that the distribution of freshwater inputs among the components of the IRL system are consistent with reality. Calibration and validation results show that both hydrodynamic and water quality model data match measured data within a limit of about 5 to 17% RMSE relative to the range of observations.

As of February 2016, model calibration for prediction of nutrient constituents such as nitrogen and phosphorus is continuing. However, calibration results thus far indicate that water quality

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of Technology Final Report, July 2016 model driven by the EFDC hydrodynamics coupled with the watershed model will provide accurate predictions relative to available dissolved oxygen and nutrient data. One indication of this is the good match between measured and model-predicted dissolved oxygen data. Dissolved oxygen levels are dependent on the levels of nutrients and the overall eutrophication process.

Model runs were focused on testing the sensitivity of the modeling scheme to the reduction of muck deposits at the mouth of Turkey Creek show that model is sensitive to potential variations in ammonium-based nitrogen flux to the water column. Model runs under various scenarios/cases were conducted to test potential water quality improvements that may result from muck dredging. Model Case 1 includes existing conditions with respect to watershed inputs, baseflows, and gauged freshwater flow into Turkey Creek from the C-1 control structure. Nutrient flux from the benthic boundary of Turkey Creek was set according to fluxes reported by Dr. John Trefry in Chapter 3 of this report. In the region surrounding Turkey Creek the flux was set to be equivalent to the IRL average. Model Case 2 assumed a 50% reduction in the ammonium-based nitrogen flux from muck sediment to the water column. Model results indicate a reduction of about 25% to 30% in total nitrogen concentration in the water column at the mouth of Turkey Creek after hypothetical reduction of ammonium flux based on muck removal. Model results also showed a detectible, but variable reduction of total nitrogen within 4 km of Turkey Creek entrance. A numerical (model) monitoring station in the IRL, 10 km to the south of Turkey Creek entrance, showed a detectible reduction in total nitrogen concentration for the first half of a 2-year model run. Other water quality variables are also calculated including forms of phosphorus, dissolved oxygen, and several others. These model data along with values for nitrogen components are stored in model data archives for further analysis

In the second year of the overall muck project, further details will be provided to guide the model, including measured nutrient flux from the benthic sediment of Turkey Creek once the muck removal is complete. In addition, the scope of work for year 2 includes setup of sediment transport calculations for sediment sizes in the silt and clay range. Sediment transport calculations, especially in the Turkey Creek area will be supported by sediment flux data being collected by other components of the overall project (Drs. Trefry and Bostater). Using longer term model runs, this calculation will provide an estimate of the return period for fine sediment constituent of muck sediment.

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5.7 References Cerco, C. F., and T. Cole. 1994. Three-dimensional eutrophication model of Chesapeake Bay. J. Environ. Eng. 119, 1006-1025.

Environmental Research & Design, Inc. 2012. Refining the Indian River Lagoon TMDL, Technical Memorandum Report: Assessment and Evaluation of Model Input Parameters. 367p.

Hamrick, J.M. 1992. A Three-Dimensional Environmental Fluid Dynamics Code: Theoretical and Computational aspects. Special Report 317 in Applied Marine Science and Ocean Engineering, Virginia Institute of Marine Science, Gloucester Point, VA 23062.

Landon, M. K., Rus, D. L., and F. E. Harvey. 2001. Comparison of Instream Methods to Measure Hydraulic Conductivity in Sandy Sediments. Ground Water 39(6) 870-885.

Lee, D. R. 1977. A device for measuring seepage flux in lakes and estuaries. Limnology and Oceanography. 22, 140-147.

Park, K., A. Y. Kuo, J. Shen, and J. M. Hamrick, 1995. A three-dimensional hydrodynamic- eutrophication model (HEM3D): description of water quality and sediment processes submodels. The College of William and Mary, Virginia Institute of Marine Science. Special Report 327.

Sigua, G., Steward, J. S., and W. A. Tweedale. 1999. Status of Water Quality in the Indian River Lagoon System: Spatial and Temporal Trends, Summary Report (1988-1994). Division of Environmental Sciences, St. Johns River Water Management District, Technical Memorandum # 33.

Sigua, G. C. and Steward, J. S. 2000. Water quality monitoring and biological integrity assessment in the Indian River Lagoon, Florida: Status, Trends and Loadings (1988-1994) Environmental Management 25: 199-209.

Sisson, G. M., J. Shen, S. C. Kim, J. Boon, and A. Y. Kuo. 1997. VIMS three-dimensional hydrodynamic-eutrophication model (HEM-3D): application of the hydrodynamic model to the York River system. VIMS (Virginia Institute of Marine Science), Special Report in Applied Marine Science and Ocean Engineering 341, Gloucester Point, VA.

St. Johns River Water Management District. 2015. Field Standard Operating Procedures for Surface Water Sampling. SJRWMD Bureau of Water Resource Information. 116 p.

Tetra Tech, 2000. Three-Dimensional Hydrodynamic and Water Quality Model of Peconic Estuary, Final Report to the Peconic Bay National Estuary Program.

Tetra Tech, 2005. Development of the Hydrodynamic and Water Quality Models for the Savannah Harbor Expansion Project. Final Report prepared for USACE – Savannah District. 101p. 5-32

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Tetra Tech, 2006. The Environmental Fluid Dynamics CodeTheory and Computation. Volume 3: Water Quality Module. 88p.

Trefry, J., Trocine, R., Fox, A., Fox, S., Voelker, J., Beckett, K. 2015. The Efficiency of Muck Removal from the Indian River Lagoon and Water Quality after Muck Removal. Presentation to Brevard County.

Sauer, V.B., and Turnipseed, D.P., 2010, Stage measurement at gaging stations: U.S. Geological Survey Techniques and Methods book 3, chap. A7, 45 p. http://pubs.usgs.gov/tm/tm3-a7/.

Turnipseed, D.P., and Sauer, V.B., 2010, Discharge measurements at gaging stations: U.S. Geological Survey Techniques and Methods book 3, chap. A8, 87 p. http://pubs.usgs.gov/tm/tm3-a8/.

Zarillo, G.A. 2003. Salinity Distribution and Flow Management Studies: A Three Dimensional Model of the Lake Worth Lagoon, FL, South Florida Water Management District, 70p.

Zarillo, G.A., 2006. Calibration of the Environmental Fluid Dynamics Code for Sebastian Inlet and Vicinity. Prepared for the Sebastian Inlet Tax District., 22p.

Zarillo, G.A. 2004. Final Report: EFDC/HEM3D Hydrodynamic and Water Quality Model of the Loxahatchee River and Estuary. Prepared For: Tetra Tech, Inc., Tallahassee, FL.

Zarillo, G.A., 2001. Lake Jesup Hydrodynamic Model. Phase II. St. Johns River Water Management District. 55p.

Zarillo, G.A., Application of a Three-Dimensional Model to Evaluate Improvements in the Long Slip Canal Entrance Basin – Hudson River, 1999. Dames and Moore, Inc., 58 p.

Zarillo, G.A., 1997. Three-Dimensional Modeling of Circulation and Flushing in the German Wadden Sea, GKSS Research Center, Geesthacth, Germany,. 45 p.

Zarillo, G.A. and Yuk, S-s., 1997. Indian River lagoon/Sebastian River Hydrodynamic and Salinity Model. St. Johns River Water Management District. 47 p.

Zarillo, G.A. and Surak, C.R. 1994. Indian River Lagoon/Turkey Creek Hydrodynamics and Salinity Model. Final Report to the St. Johns River Water Management District. 145 pp.

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